Every few months a lifter argues on Reddit that "FFMI 25 is bro science" — a made-up number lifters throw around to accuse each other of steroid use. The counter-argument is usually a link to a Wikipedia summary and a vague "there's a study."
The study exists, and it is worth reading beyond the summary. Kouri et al. published "Fat-free mass index in users and nonusers of anabolic-androgenic steroids" in the Clinical Journal of Sport Medicine in 1995. It is the paper the FFMI 25 ceiling comes from, and the methodology is more careful than the internet gives it credit for. Here is what they actually did, what the number means, and what it does not mean.
The setup
The researchers wanted a defensible way to compare muscularity between athletes without letting fat mass or body size distort the comparison. Two problems they were solving:
- BMI cannot tell muscle from fat. A 100 kg powerlifter and a 100 kg sedentary adult get the same BMI. Useless for physique science.
- Raw bodyweight favors taller athletes. A 90 kg lifter at 190 cm is less muscular than a 90 kg lifter at 170 cm. Weight alone does not scale.
Their solution was Fat-Free Mass Index (FFMI):
def ffmi(weight_kg, height_m, body_fat_pct):
lean_body_mass = weight_kg * (1 - body_fat_pct / 100)
raw_ffmi = lean_body_mass / (height_m ** 2)
normalized = raw_ffmi + 6.1 * (1.8 - height_m)
return raw_ffmi, normalized
The + 6.1 * (1.8 - height_m) term corrects for the geometric bias in any "divided by height squared" metric — without it, shorter lifters look artificially more muscular than tall ones.
The sample
157 male subjects, all recruited from gyms in the Boston area:
- 83 nonusers of anabolic-androgenic steroids (AAS), self-reported and cross-verified with training partners and gym staff
- 74 users of AAS at the time of measurement or in the year prior
The nonuser group was the critical dataset. If the researchers could measure the top of the distribution in verified drug-free lifters, they would have a defensible ceiling.
Body composition was measured via underwater weighing (hydrostatic densitometry) — the accepted gold standard in 1995, more accurate than skinfold calipers and roughly comparable to modern DEXA.
The result
The nonusers had a mean FFMI of 21.8 with a standard deviation of ~1.8. The top of the distribution:
- Highest FFMI in the nonuser group: 25.0
- Second-highest: 24.8
- Third-highest: 24.6
Every AAS user above FFMI 25 was in the user group. Not a single verified natural lifter in the sample exceeded 25.
Kouri et al. then compared this against historical data on pre-steroid-era bodybuilders (Steve Reeves, John Grimek, Reg Park) recalculated from photographs and reported stats. Grimek came out at approximately FFMI 25.4, at the edge but consistent with the modern natural distribution.
The conclusion in the paper's own words: "FFMI represents a useful measurement of muscularity, and it may be a useful adjunct in the evaluation of individuals suspected of steroid abuse."
Why the number has held up 30 years later
The Kouri number could have been dismissed as an artifact of a small 1995 sample. It has not been, because subsequent research keeps landing in the same neighborhood.
- Helms et al. 2014 (natural bodybuilding contest preparation review): natural competitors at stage weight cluster at FFMI 21-23, with elite competitors reaching 24-25.
- Kuipers et al. 2016 (anabolic-agent detection review): confirmed FFMI 25 as a defensible upper bound for drug-free lifters in ~30 years of accumulated data.
- Modern DEXA-verified studies in trained natural bodybuilders (e.g., Chappell 2018) find the same ceiling.
Individual outliers exist. A handful of natural lifters have posted verified FFMIs at 25.0-25.5 with photographic evidence, DEXA verification, and long training histories. But 26+ in a verified natural context remains statistically absent from the literature.
What the number means
It means: for the vast majority of natural male lifters, FFMI 25 is the observed upper bound of what is achievable across 10-20 years of consistent training. Reaching 23-24 is elite. Sitting at 21-22 after 5+ years of training is normal. FFMI 25 is not a target — it is a ceiling that fewer than 1 in 1000 natural lifters ever touch.
It does not mean: anyone above FFMI 25 is definitely using steroids. The number is statistical, not diagnostic. A genetic outlier at 25.3 with legitimate long training history is possible. What Kouri showed is that it is rare, not impossible.
Doing the math on yourself
The full formula chain:
def compute_ffmi(weight_kg, height_cm, body_fat_pct):
height_m = height_cm / 100
lean_body_mass = weight_kg * (1 - body_fat_pct / 100)
raw = lean_body_mass / (height_m ** 2)
normalized = raw + 6.1 * (1.8 - height_m)
return {
'lean_body_mass_kg': round(lean_body_mass, 1),
'raw_ffmi': round(raw, 2),
'normalized_ffmi': round(normalized, 2)
}
# Example: 80 kg, 180 cm, 15% body fat
compute_ffmi(80, 180, 15)
# {'lean_body_mass_kg': 68.0, 'raw_ffmi': 20.99, 'normalized_ffmi': 20.99}
The two numbers are identical at exactly 180 cm because the normalization term goes to zero there. At 170 cm the normalized FFMI runs higher than raw; at 190 cm it runs lower. This is the correction that lets you compare a 170 cm lifter to a 190 cm lifter fairly.
For interpretation, the standard benchmarks by training experience:
| FFMI (normalized) | Level |
|---|---|
| 17-18 | Untrained baseline |
| 19-20 | Beginner, first 12 months |
| 21-22 | Multi-year natural lifter |
| 23-24 | Advanced natural |
| 25 | Kouri ceiling (elite natural) |
| 26+ | Statistically inconsistent with drug-free training |
For women, subtract roughly 3 points at each level — the natural ceiling for female lifters lands around FFMI 22.
Where the study is limited
Being fair to the paper's actual scope:
- Sample size (157) is small by modern standards. Larger cohorts would tighten the confidence interval on where the ceiling sits — but every replication has landed in the same 24-25 zone, so the direction is robust even if the exact number moves ±0.5.
- Self-reported drug use is a real weakness. Some "nonusers" may have used steroids and lied. This would push the true natural ceiling lower, not higher — the observed 25.0 is an upper bound of self-reported nonusers, so it is if anything conservative.
- Male-only sample. The female FFMI ceiling of ~22 comes from smaller subsequent studies, not this one.
- Hydrostatic weighing has ±2% body-fat error, which propagates to ±0.3-0.5 FFMI. Modern DEXA is tighter but not zero-error.
None of these limitations invalidate the finding. They just mean the exact number should be treated as "roughly 25" rather than "exactly 25.0."
What to do with this
Two takeaways:
If your FFMI is 22 and you have been training for four years, you are doing fine. The gym-Instagram culture makes 25 feel like a baseline. It is not. It is elite territory.
If someone claims a verified natural FFMI of 27, they are almost certainly wrong — either about the FFMI calculation (using raw instead of normalized) or about the natural part. Kouri did not prove it is impossible, but he did prove it is vanishingly rare.
Full breakdown with the Kouri methodology quotes and the follow-up literature is at ffmicheck.com/blog/natural-genetic-muscle-limit-science/. If you want to run your own number without pen and paper, the FFMI calculator does the raw + normalized math in one step.
Related from earlier posts on this profile: Why every TDEE calculator gives you a different number (the same "formulas that quietly disagree" damar, applied to metabolism instead of muscularity) and The two 1RM formulas that give different answers.
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