Free PM calculator · Schedule risk
Monte Carlo Schedule Simulator
Enter three-point estimates for tasks done one after another. The simulator runs thousands of random scenarios and shows how likely you are to finish by any date: P50, P80, P90 and the chance of meeting your deadline.
| Task | Optimistic | Most likely | Pessimistic |
|---|
Why use Monte Carlo for schedules?
Adding up "most likely" estimates gives a plan that you will usually miss, because delays add up faster than savings. Monte Carlo simulation picks a random duration for every task, within your optimistic and pessimistic range, thousands of times. The result is a probability curve: how likely you are to finish by each possible date.
P80 = the value 80% of runs finish within
How to use the results
- Commit to P80 or P90 for external dates, and plan internally to P50.
- The gap between the single-point plan and P80 is a good basis for schedule contingency.
- If the chance of meeting the deadline is low, look at the tasks with the widest ranges first. Reducing their uncertainty helps most.
Limits of this simulator
Tasks are treated as one sequence with no parallel paths, and as independent of each other. Real schedules have parallel paths that merge, which makes delays even more likely. For networks of tasks, find the critical path with the PERT/CPM tool first, then simulate that path here.
Related: Monte Carlo simulation, quantitative risk analysis, PERT estimate calculator.