b2KIT

Retirement Savings Planner

Model retirement savings with Monte Carlo simulations of market returns. Visualize probability of achieving target nest egg.

Tested tool guide Tested browser tools Checked August 16, 2026

What Retirement Savings Planner does and how it behaves

Saving a fixed amount each year does not produce a fixed nest egg. This tool runs Monte Carlo simulations: it generates thousands of market futures, each with its own randomly drawn yearly returns, compounds your savings through every one, and reports what share of those futures reaches your target. The output is a probability plus a range of possible ending balances, not a single promised number. The thing most users get wrong is trusting the average path: a plan can look fine at 8 percent per year while the lower tail of outcomes falls far short. The order of good and bad years matters as much as the average.

How the result is produced

1

How one simulated future is built

Each run of the model creates a large number of independent hypothetical futures, one per simulation. In every simulated year the portfolio grows by a return drawn at random from a distribution of possible returns, then that year's contribution is added to the balance. Following a single future to retirement produces one ending balance, and the full set of endings is the raw output of the exercise.

2

Where the probability comes from

Once all futures finish, the tool sorts the ending balances and counts the fraction that reached the target nest egg. That fraction is the reported probability of success. The sorted list also shows how outcomes spread, from poor-market to good-market, so the plan gets a range rather than a single figure. The random draws change on every run, so the percentages move a little each time.

Good uses

  • You are deciding whether your current monthly contribution gets you to a chosen target nest egg by retirement, and want a probability rather than a guess.
  • You are comparing options - bigger contributions, a later retirement age, or a smaller target - and want to see how each moves the odds, not just the average balance.
  • You are near retirement and planning withdrawals, and want to see how much a bad stretch of markets right after you stop working cuts your chances.

Limits and checks

  • The probability is an estimate from a finite number of simulated futures, so running the tool twice gives slightly different numbers. Treat the result as a ballpark, and prefer the shape of the distribution over the exact percentage.
  • The model runs entirely in your browser on the assumptions you type. It pulls no current market, inflation, or tax data from anywhere, and it will not second-guess a rosy expected return - the result is only as meaningful as the inputs.
  • Every future in the simulation assumes you follow the plan exactly: contributions on schedule, no early withdrawals, no panic selling. The tool models market randomness, not your behavior, so a high probability is not a promise that you will stay on course.

Common questions

What does a 70 percent probability of success actually mean?

In about seven of every ten simulated futures, the balance reached your target, and in three it fell short. It is a statement about the model's market assumptions, not a guarantee about your real retirement. The percentage is also a sample estimate - run the tool again and it shifts slightly - and it assumes you follow the plan exactly.

Why is my result lower than the straight-line projection I can compute by hand?

The straight line compounds every year at the exact average return, which is the single best-case order of returns. Real markets deliver good and bad years in some sequence, and a bad sequence early, especially once withdrawals start, leaves a much smaller balance even when the average return is identical. The gap between the straight line and the median simulated outcome is the sequence-of-returns risk this tool is for.

References and verification

The behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.

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