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Monte Carlo Project Forecaster
Enter three-point estimates for each task, run thousands of simulated project outcomes, and replace a single indefensible date with a confidence-based forecast you can actually commit to.
The sum of your "most likely" estimates is your optimistic case, not your plan.
Risk is asymmetric. Tasks blow out far more than they come in early, so adding up most-likely values produces a date the project rarely hits. Commit to a confidence level instead, like the P85 date below.
Forecast summary
Running the first simulation…
Tasks
✓ Auto-savedOptimisticMost likelyPessimistic
All values in days. Tasks are simulated sequentially in v1, with no parallel work.
Simulation settings
Distribution
Triangular treats the three estimates as a simple triangle of probability.
JSON round-trips the full task list and settings. CSV includes the percentile summary and every run result.