Setting up the test scenario
To see what the simulator actually produces, we ran it against a common scenario: a 200 lb starting weight, a 170 lb goal, moderate activity, a 500-kcal daily deficit, and a self-reported adherence pattern of 5 out of 7 days on-target with occasional travel.
The headline numbers
Across 1,000 trials, the "most likely" (50th percentile) outcome landed around week 19-21 -- noticeably later than the naive linear estimate of roughly 12 weeks that a 500-kcal deficit and 30 lb loss would suggest on paper. The 90th-percentile "worst realistic case" pushed well past week 27.
Why the spread matters more than the midpoint
The gap between the 10th and 90th percentile in this run was over two months. That's the practical value of Monte Carlo modeling over a single-point estimate: it quantifies how much uncertainty your specific adherence pattern introduces, rather than hiding it behind one falsely precise date.
What changed the result the most
Re-running the same scenario with 7-out-of-7 adherence shifted the median outcome earlier by several weeks and narrowed the probability band substantially. Re-running with 3-out-of-7 adherence pushed a meaningful share of trials past the 2-year simulation ceiling entirely -- illustrating just how much real-world consistency matters compared to the deficit number alone.