May 22, 2026

How Many Calories Should I Eat to Lose Weight? A 2026 Guide With Formulas and Safe Deficit Ranges

TL;DR: Most adults lose roughly 1 pound per week with a 500 kcal/day deficit below their total daily energy expenditure (TDEE). The Academy of Nutrition and Dietetics recommends the Mifflin–St Jeor equation for estimating resting metabolic rate in general adults, paired with an activity multiplier to get TDEE. The safest sustained rate is 0.5–1% of body weight per week; deeper cuts accelerate scale weight loss but cost lean mass, energy, and hormonal stability. Use the formulas here as a starting point and adjust weekly based on actual progress.


Table of Contents

  1. How to Calculate Your Calorie Needs in 2026
  2. From RMR to TDEE: Activity Multipliers Explained
  3. What Counts as a Safe Calorie Deficit?
  4. When Cutting Too Aggressively Backfires
  5. Why Static Calculators Get You Started, but Adaptive Targets Get You Results
  6. FAQ

How to Calculate Your Calorie Needs in 2026

The standard process is two steps: estimate resting metabolic rate (RMR) — the calories your body burns at complete rest — then multiply by an activity factor to get total daily energy expenditure (TDEE). Subtract from TDEE to create a deficit.

Mifflin–St Jeor (recommended for general adults)

The Academy of Nutrition and Dietetics recommends the Mifflin–St Jeor equation as the primary RMR prediction equation for general adults, including individuals with overweight or obesity, because it has historically demonstrated higher accuracy than alternatives, accurately predicting RMR in roughly 70–82% of individuals in cross-validation work, compared with 38–80% for Harris–Benedict (Flack et al., 2016; Bakır & Cebioğlu, 2024).

Mifflin–St Jeor (metric):

  • Men: RMR = (10 × weight in kg) + (6.25 × height in cm) − (5 × age) + 5
  • Women: RMR = (10 × weight in kg) + (6.25 × height in cm) − (5 × age) − 161

Mifflin–St Jeor (US units):

Convert first: weight in kg = lb ÷ 2.205; height in cm = inches × 2.54.

Harris–Benedict (revised 1984)

Harris–Benedict is the older and more widely-cited equation. The original 1918 version overestimates in modern populations; most calculators use the 1984 Roza-Shizgal revision.

  • Men: RMR = 88.36 + (13.40 × weight in kg) + (4.80 × height in cm) − (5.68 × age)
  • Women: RMR = 447.59 + (9.25 × weight in kg) + (3.10 × height in cm) − (4.33 × age)

Which equation should you use?

For most adults, Mifflin–St Jeor is the better default. Research consistently shows it has the lowest overestimation in adults with overweight and obesity compared with Harris–Benedict, FAO/WHO/UNU, and Owen equations (Maury-Sintjago et al., 2023). However, no prediction equation is perfect: a 2023 study in Nutrients of 3,001 participants found that all common equations underestimated RMR at the individual level, with the Mifflin–St Jeor underestimating by an average of 12.6% versus indirect calorimetry (Kfir et al., 2023). A 2023 systematic review and meta-analysis in Sports Medicine found that in athletes specifically, the Ten-Haaf equation outperformed Mifflin–St Jeor, predicting 80.2% of athletes within ±10% of measured RMR versus 40.7–63.7% for the other equations (O'Neill et al., 2023).

What to do in practice? Start with Mifflin–St Jeor, then adjust based on your weight trend after 2–3 weeks. That iterative correction matters more than which equation you choose initially.

From RMR to TDEE: Activity Multipliers Explained

RMR is what you burn at complete rest. TDEE adds the calories burned through daily movement and exercise. Multiply your RMR by the activity factor that matches your reality:

Activity LevelMultiplierDescription
Sedentary1.2Desk job, little to no exercise
Lightly active1.375Light exercise 1–3 days/week, or active job
Moderately active1.55Moderate exercise 3–5 days/week
Very active1.725Hard exercise 6–7 days/week
Extra active1.9Physical job + daily training, or twice-daily training

The single most common mistake is overestimating activity level. A 30-minute walk three times a week is "lightly active," not "moderately active." If you spend most of the day sitting and train 3–4 hours per week, use 1.375. The honest answer keeps your calculation realistic.

TDEE = RMR × activity multiplier

To create a deficit:

  • Subtract 500 kcal/day → ~1 lb/week loss
  • Subtract 750 kcal/day → ~1.5 lb/week loss (use with caution if you have less than 30 lb to lose)
  • Subtract 250 kcal/day → ~0.5 lb/week loss (best for leaner individuals or recomposition)

But remember, real-world weight loss curves flatten as your body adapts, which is why even a "perfectly calculated" deficit slows down over time and needs adjustment.

What Counts as a Safe Calorie Deficit?

There are three boundaries every weight-loss target should respect (If you're new to the concept itself, our guide to what a calorie deficit is covers the fundamentals first):

1. Rate ceiling: 0.5–1% of body weight per week. Peer-reviewed research consistently shows that slower rates of weight loss (≤0.5–1% of body mass per week) attenuate unfavorable adaptations and lean mass loss (Roberts et al., 2020). For a 180-lb person, that's roughly 0.9–1.8 lb per week — and the bottom of that range is usually the better choice for body composition.

2. Absolute floor: ~1,200 kcal/day for women, ~1,500 kcal/day for men. Below these thresholds, micronutrient adequacy becomes very difficult to achieve through food alone, and the risk of sustained metabolic and hormonal disruption rises sharply.

3. Deficit percentage: aim for 15–25% below maintenance. A 500 kcal/day deficit is roughly 20–25% below maintenance for most adults, which is the range with the most evidence for sustainable fat loss combined with lean mass preservation.

It's common to want to lose weight as quickly as possible, but faster scale-weight loss usually costs more lean mass. A study comparing two rates of weight loss in trained women (1 kg/week at a 1,100 kcal deficit versus 0.5 kg/week at a 550 kcal deficit) found the faster group experienced a significant reduction in testosterone and an increase in sex hormone binding globulin, even on matched protein intake (Hector & Phillips, 2018, citing Mero et al., 2010). In practical terms, these hormonal shifts impair muscle preservation, recovery, and energy, which is why the scale may drop faster but the body composition outcome is worse.

When Cutting Too Aggressively Backfires

Faster bodyweight loss is possible, but the composition of that loss shows why it's almost never a good idea. Across weight-loss interventions, roughly 10–25% of total weight lost is muscle mass (Heymsfield et al., as cited in Bolte et al., 2025). When deficits are too aggressive, that proportion goes up, and so do the downstream consequences:

  • Lower resting metabolic rate. Resting energy expenditure drops by about 13 kcal/day for every kilogram of muscle lost, versus only 4.5 kcal/day per kilogram of fat lost. Aggressive cuts that strip muscle make future maintenance harder.
  • Hormonal disruption. Faster rates of loss have been associated with drops in testosterone, increases in cortisol, and menstrual cycle disruption in women (Hector & Phillips, 2018; Schöenfeld et al., 2023).
  • Compensatory hunger. Loss of lean mass drives compensatory hyperphagia — the body increases drive to eat in an effort to restore the lost tissue, which sets up the rebound cycle.
  • Plateau acceleration. Adaptive thermogenesis means a 500 kcal deficit calculated today is not a 500 kcal deficit three months from now. The bigger the initial cut, the steeper the adaptation curve.

The most muscle-protective combination includes a slower rate of loss, adequate protein (1.6–2.2 g/kg/day during a deficit), and resistance training. This combination has been shown to preserve, and in some cases increase, lean mass even during meaningful caloric deficits (Hector & Phillips, 2018). Hitting that protein target consistently is easier with a macro tracker built for high-protein eating.

Why Static Calculators Get You Started, but Adaptive Targets Get You Results

Every formula in this article (Mifflin–St Jeor, Harris–Benedict, the activity multipliers) is just a starting point. The peer-reviewed evidence is unambiguous: no equation predicts RMR perfectly at the individual level, and most underestimate it in the general population by 8–17% (Kfir et al., 2023). On top of that, your TDEE itself changes as you lose weight, as your activity habits drift, and as your metabolism adapts to a sustained deficit.

This is especially true for specific populations — for instance, active adults over 60 face unique calorie calculation challenges where a one-size-fits-all 500-kcal cut can backfire.

That's why the most useful thing a nutrition app can do is adjust your calorie target based on what's actually happening to your weight, not lock you into the number the calculator spit out on day one.

This is the core design choice behind Fitia's adaptive algorithm: the app uses Mifflin–St Jeor as its starting equation, then recalculates your calorie and macro targets based on your real progress data, including weight trend, logged intake, and goal pace. If you're losing faster than planned, it raises calories. If you've stalled for two weeks, it adjusts down. The static-formula approach treats your metabolism as fixed, but the adaptive approach treats it as the moving target it actually is.

Start your free Fitia trial to get a calculated calorie target that adjusts as your body changes, without spreadsheets or manual recalculation when you plateau.

FAQ

How many calories should I eat to lose 1 pound a week? 

About 500 kcal/day below your TDEE. For most adults, this lands between 1,400–2,400 kcal/day depending on sex, body size, and activity. Calculate your TDEE using the Mifflin–St Jeor equation multiplied by an activity factor, then subtract 500.

What's the formula for calories per day to lose weight? 

The standard approach is TDEE = Mifflin–St Jeor RMR × activity multiplier, then subtract 500 kcal/day for ~1 lb/week loss. For men: RMR = (10 × kg) + (6.25 × cm) − (5 × age) + 5. For women: RMR = (10 × kg) + (6.25 × cm) − (5 × age) − 161.

Mifflin–St Jeor vs. Harris–Benedict — which is better? 

The Academy of Nutrition and Dietetics recommends Mifflin–St Jeor for general adults because it has the lowest overestimation in adults with overweight and obesity. Harris–Benedict is acceptable but tends to overestimate slightly more. Neither equation is perfect at the individual level; both should be treated as starting points.

What is a safe calorie deficit for weight loss? 

A safe deficit is 15–25% below maintenance (typically 250–750 kcal/day) producing a rate of 0.5–1% of body weight per week. Stay above ~1,200 kcal/day for women and ~1,500 kcal/day for men in sustained dieting unless under direct medical supervision.

Is 1,200 calories too low? 

For most adults, yes — sustained intake below ~1,200 kcal/day for women or ~1,500 kcal/day for men is hard to make nutritionally adequate and increases the risk of lean mass loss, hormonal disruption, and rebound eating. If your calculated deficit lands here, raise activity or extend the timeline instead of cutting further.

How fast can I safely lose weight? 

0.5–1% of body weight per week is the evidence-based range that minimizes lean mass loss and metabolic adaptation. Faster scale loss is possible but typically costs more muscle and is harder to sustain. Athletes and lean individuals should stay at the lower end.

Does Fitia calculate my calorie deficit automatically? 

Yes. Fitia uses Mifflin–St Jeor as its base equation, then adapts your calorie and macro targets based on your real weight-trend and logged-intake data — so when your body adapts or you plateau, the target adjusts instead of you having to recalculate manually.

Want a starting target that actually updates as your body changes? Download Fitia and use code FITIANOW to save on Premium.


About the Author

Author's profile pictureFiorella Ricardi is a licensed nutritionist from Universidad Científica del Sur, where she graduated in the top fifth of her class. She brings hands-on experience across clinical, public health, and food service nutrition. For the past two years, she has worked at Fitia as Operations Lead, focused on improving the accuracy of internal food entry data and ensuring users see correct, reliable nutritional insights inside the app.

References

  • Flack, K. D., Siders, W. A., & Johnson, L. P. (2016). Cross-Validation of Resting Metabolic Rate Prediction Equations. Journal of the Academy of Nutrition and Dietetics, 116(9), 1413–1422. https://doi.org/10.1016/j.jand.2016.03.018
  • Pavlidou, E., Papadopoulou, S. K., & Seroglou, K. (2023). Revised Harris–Benedict Equation: New Human Resting Metabolic Rate Equation. Metabolites, 13(2), 189. https://doi.org/10.3390/metabo13020189
  • Maury-Sintjago, E., Rodríguez-Fernández, A., & Ruíz-De la Fuente, M. (2023). Predictive Equations Overestimate Resting Metabolic Rate in Young Chilean Women with Excess Body Fat. Metabolites, 13(2), 188. https://doi.org/10.3390/metabo13020188
  • Bakır, B. O., & Cebioğlu, İ. K. (2024). Accuracy of the Resting Metabolic Rate Equations. Research Square preprint. https://doi.org/10.21203/rs.3.rs-5286778/v1
  • Kfir, A., Lahav, Y., & Gepner, Y. (2023). Cross-Validation of a New General Population Resting Metabolic Rate Prediction Equation Based on Body Composition. Nutrients, 15(4), 805. https://doi.org/10.3390/nu15040805
  • O'Neill, J. E. R. G., Corish, C., & Horner, K. (2023). Accuracy of Resting Metabolic Rate Prediction Equations in Athletes: A Systematic Review with Meta-analysis. Sports Medicine, 53(12), 2373–2398. https://doi.org/10.1007/s40279-023-01896-z
  • Bolte, J., Smelter, A. A., & Norton, L. (2025). Are we giving too much weight to lean mass loss? Molecular Metabolism, 101, 102253. https://doi.org/10.1016/j.molmet.2025.102253
  • Hector, A. J., & Phillips, S. M. (2018). Protein Recommendations for Weight Loss in Elite Athletes: A Focus on Body Composition and Performance. International Journal of Sport Nutrition and Exercise Metabolism, 28(2), 170–177. https://doi.org/10.1123/ijsnem.2017-0273
  • Roberts, B. M., Helms, E. R., & Trexler, E. T. (2020). Nutritional Recommendations for Physique Athletes. Journal of Human Kinetics, 71(1), 79–108. https://doi.org/10.2478/hukin-2019-0096
  • Schöenfeld, B. J., Androulakis-Korakakis, P., & Piñero, A. (2023). Alterations in Measures of Body Composition, Neuromuscular Performance, Hormonal Levels, Physiological Adaptations, and Psychometric Outcomes during Preparation for Physique Competition: A Systematic Review of Case Studies. Journal of Functional Morphology and Kinesiology, 8(2), 59. https://doi.org/10.3390/jfmk8020059

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