Retirement Monte Carlo Calculator (Success Probability)
A single average return hides the thing that actually breaks retirement plans: bad years arriving at the wrong time. This calculator simulates 5,000 possible market futures for your plan — saving until you retire, then spending until your plan horizon — and reports the share of paths where the money never runs out. Everything is in today's dollars, so enter a real (inflation-adjusted) return. The fan chart shows the 10th, 50th, and 90th percentile balance at every age. It is a planning model, not financial advice.
Your plan
Everything is in today's dollars: use a real (inflation-adjusted) return. 5,000 seeded market paths are simulated, so identical inputs always give identical results.
Plan success probability
65.7%
of 5,000 simulated paths still have money at age 95
P10 at 65
$570,266
Median at 65
$1,169,671
P90 at 65
$2,570,916
Balance fan — 10th percentile vs median
Percentiles by age
Median ending balance at 95: $849,151 (failed paths count as $0).
Compare scenarios
Run the same calculation with two or three input sets side by side. Differences are highlighted; every number comes from the same tested formula as the calculator above.
| Input | Scenario A | Scenario B |
|---|---|---|
| Current Age | ||
| Retire Age | ||
| Current Savings | ||
| Monthly Contribution | ||
| Expected Real Return Pct | ||
| Volatility Pct | ||
| Monthly Retirement Spending | ||
| Plan Until Age |
How it works
Each simulated path draws one random real return per year from a normal distribution with your expected return as the mean and your volatility as the standard deviation. Before retirement, the balance grows by that year's return and then receives twelve monthly contributions, credited at year end. After retirement, the balance grows and then pays out twelve months of spending. If a path's balance ever drops below zero, that path has failed and stays failed — the success probability is simply the share of the 5,000 paths still solvent at your plan-until age.
The simulation is seeded, so the same inputs always produce exactly the same answer — useful for comparing scenarios: change one input and any shift in the success probability is caused by that input, not by random noise. The fan chart summarizes all 5,000 paths at each age with three percentiles: 10% of paths end up below the p10 line, half below the median, and 90% below the p90 line. The gap between p10 and p90 widening over time is volatility compounding — the honest picture a single-average calculator cannot show.
Because the model runs in today's dollars with a real return, the spending you enter keeps today's purchasing power automatically. What counts as a 'good' success probability is a judgment call: many planners aim for 80–90% rather than 100%, since pushing to certainty demands much more saving while real retirees can adjust spending in bad markets. Note the asymmetry the fan chart reveals: the median outcome is usually well below the straight-line compound-interest projection, because volatility drags compounded growth down even when the average return is unchanged.
Frequently asked questions
How realistic is this Monte Carlo model?+
It is deliberately simple: annual returns are drawn independently from a normal distribution, identically every year. Real markets are messier — returns have fat tails (extreme years happen more often than a normal distribution predicts), bad years cluster, and valuations influence future returns. That means this model can understate the risk of severe crashes and overstate the independence of consecutive years. Treat the success probability as a rough gauge for comparing scenarios, not a precise forecast, and stress-test with a lower return and higher volatility than you expect. This is not financial advice.
What return and volatility should I enter?+
Use a real (inflation-adjusted) return, because the model keeps everything in today's dollars. Historically a diversified stock-heavy portfolio has delivered roughly 4–7% real with volatility around 15–18%; adding bonds lowers both. Past averages are not guarantees, and many analysts expect future returns below historical norms, so a conservative pairing — say 4–5% real with 15% volatility — is a reasonable starting point. Whatever you choose, vary it: if your plan only works at 7% real, the plan is fragile. The result reflects your assumptions, not a prediction.
Is 85% success good enough? What does failure actually mean?+
In the model, failure means the simulated balance hits zero before your plan-until age. In real life it rarely looks like that: people notice the portfolio shrinking and cut spending, work part-time, downsize, or annuitize — and Social Security or pensions usually provide a floor this tool does not model. That is why many planners consider 80–90% acceptable rather than demanding 100%, which forces heavy oversaving for scenarios you could adapt your way out of. Use the number to compare plans and spot fragility, and revisit it as your balance and assumptions change. This is a planning estimate, not advice.