Monte Carlo Retirement Simulation Software: What to Look For

3.9%. Morningstar's 2025 research puts the safe starting withdrawal rate for a 30-year retirement at 3.9%. It judged that number by whether the money was still there in 90% of simulated futures, not by an average return (Morningstar, The State of Retirement Income 2025, Dec 2025). That kind of test is what Monte Carlo retirement simulation software runs on your own numbers.

So what should you look for? Here's the short answer. A good tool:

• gives you a probability, not one tidy projection
• tells you how it models market returns
• runs your plan well into your 90s
• treats health care as a real cost
• lets you stress-test your spending
• asks for only the data it needs

The rest of this guide shows how to check each of those.

What Monte Carlo retirement simulation software actually does

A fixed-rate calculator assumes your portfolio earns the same return every year, often around 6% or 7%. Real markets don't behave that way. A bad first few years can do lasting damage, even if the long-run average looks fine. This is called sequence-of-returns risk.

Monte Carlo simulation deals with that by playing out your retirement many times. Each run uses a different random sequence of market years. Then the software counts how many of those runs ended with money left.

If 870 out of 1,000 runs stay funded, your success rate is 87%.

That number is a probability, not a promise. It's also a better answer than "you'll have $1.2 million at 85," because it shows you how wide the range of outcomes is.

Seven things to look for in Monte Carlo retirement software

1. A success rate, not an average-return projection

Start by checking whether the tool runs Monte Carlo at all. Many popular calculators don't. Comparison roundups from Gerald list NerdWallet and AARP as tools without Monte Carlo. FI Calc and Rich Broke or Dead use historical backtesting, which replays actual past market periods rather than random ones. Boldin and ProjectionLab offer Monte Carlo.

Backtesting is still useful. It just answers a different question: "Would my plan have survived the past?" Monte Carlo asks: "How many plausible futures does my plan survive?"

2. Clear information on how returns are modeled

This is the detail most comparison articles leave out, and it changes the answer.

Tools generate random market years in different ways:

• Normal-distribution models draw returns from a bell curve. Critics say this underweights rare crashes, the "fat tails."
• Historical bootstrapping samples real past years at random. RetireSure Simulator, for example, runs 10,000 simulations on U.S. market returns from 1950 to 2025. An open-source command-line tool called "retire" samples historical returns from 1926 to 2024.
• Fixed-rate models aren't Monte Carlo, even when the interface looks sophisticated.

The data window matters too. A sample that starts in 1926 includes the Great Depression. One that starts in 1950 doesn't. Look for software that tells you which method and which years it uses.

3. A sensible number of runs, and a sense of proportion about it

Some tools run 1,000 simulations. Boldin's Monte Carlo, available in its paid PlannerPlus tier, runs 1,000 iterations. Others run 10,000.

More runs give a smoother, more stable estimate. But run count matters much less than the assumptions underneath it. Ten thousand runs on optimistic inputs is still optimistic. Check the assumptions before you compare run counts.

4. A horizon that takes longevity seriously

According to the Social Security Administration, about one in three 65-year-olds may live to 90 or beyond (SSA, Retirement Information for Medicare Beneficiaries, 2026).

A plan that stops at 85 quietly bets against a third of retirees. Check the default end age in any tool you try, and check whether you can change it. If the software doesn't show you the end age, assume it's too short.

5. Health care counted as its own cost

Fidelity's 2025 estimate puts health care costs in retirement at $172,500 for one 65-year-old retiring this year. That covers Medicare premiums, deductibles and prescriptions, and it leaves out long-term care entirely (Fidelity Investments, 2025 Retiree Health Care Cost Estimate, Jul 2025).

Software that folds health care into one flat spending number can understate it. Better tools model it as its own line item that changes over time.

6. Stress tests and flexible spending

Most headline success rates assume you spend the same inflation-adjusted amount every year, regardless of what markets do. Real retirees don't. They cut back after a bad year and spend a bit more after a good one.

Look for software that lets you:

• test a lower spending level, or an earlier or later retirement age
• see what happens if markets go badly in the first few years
• try spending rules such as "guardrails," which lower withdrawals when the portfolio falls and raise them when it recovers

A tool that only gives you one number and no way to push on it isn't much of a planning tool.

7. Privacy you can actually see

Some tools ask you to link your bank and brokerage accounts. Others run on a few typed-in numbers. SwitchWize notes that Monte Carlo tools often require either very basic inputs or linked accounts.

Neither approach is wrong. But you should know where your data goes, whether it's stored, and whether you can get an answer before handing anything over.

Comparing the main types of tools

Pricing models also vary. RetireSure is a one-time purchase with no subscription. MCRetire 1.2 was reviewed by AAII at $29 with a 30-day free trial. Boldin keeps Monte Carlo behind a paid tier. Prices change and vendor pages don't always agree with each other, so check the current price on the vendor's own site before you buy.

How to read the success rate once you have it

A widely used benchmark is 90% or higher. ChooseFI uses it, and Morningstar's 3.9% figure is judged by the same 90% standard.

Here's what the numbers mean in practice:

• 95%: Your plan survives almost every simulated future. You may be able to spend more than you think, or retire a bit earlier.
• 85%: Roughly one future in seven runs short. That isn't a failing grade, but you should look at what those failing futures have in common.
• Below 75%: The plan probably needs changes to spending, timing or savings.

Also ask how badly the failing runs fail. Running out at 94 is a very different problem from running out at 78. Good software shows you the spread of outcomes, such as a median result plus a worst-10% and best-10% band, not just one percentage.

The honest limits of Monte Carlo

No simulation is better than what you put into it. AAII's review of MCRetire warned that results depend on the user's inputs and that the program makes "arguably erroneous assumptions." That warning applies to every tool in this category.

There's also a real debate about which direction the errors go:

• Fat-tail critics say bell-curve models underestimate crashes, which makes Monte Carlo too optimistic.
• Kitces Research found the reverse in one analysis. 6.5% of Monte Carlo scenarios were worse than the worst historical case, so a 93.5% Monte Carlo success rate was roughly equal to 100% success on actual history.

That's one practitioner's analysis, not the final word. The practical lesson is to treat the success rate as a guide to your odds, then test it by changing your inputs.

Where Monte Climb fits

We built Monte Climb for people who want this kind of answer without hiring an advisor. You enter three numbers: your age, what you've saved for retirement, and what you spend each month. We run them through 1,000 simulated futures and return one success rate.

A few design choices follow from the research above:

• Plans run to age 95 by default, and you can push them further.
• Medicare premiums and income-based surcharges are charged year by year, not as a flat guess.
• It runs in your browser. Nothing is saved until you say so.
• William, our AI planner, answers follow-ups like "Am I on track?", "Can I retire at 62?" and "What's a sustainable spend?" You can talk to him like you would a friend, and he shows his work.

It's planning software, not advice. The full app runs on the same engine, and you can try it for 7 days for $1.

That first step matters. EBRI's 2025 Retirement Confidence Survey found 48% of workers have never estimated the monthly income they'll need in retirement (EBRI/Greenwald, Retirement Confidence Survey 2025, Fact Sheet 3). Half are guessing.

Run your own numbers

Three numbers. 1,000 futures. One probability.

Show my answer, then ask William what would move it.

Frequently asked questions

What is Monte Carlo retirement simulation software?

It's software that plays out your retirement hundreds or thousands of times, each with a different random sequence of market returns, and then reports the share of those futures in which your money lasts. That share is your success rate. A fixed-rate calculator assumes the same return every year instead.

What is a good Monte Carlo success rate for retirement?

A common benchmark is 90% or higher. ChooseFI uses it, and Morningstar's 2025 safe withdrawal rate of 3.9% is judged by the same 90% standard. A success rate is a probability, not a guarantee, so look at how badly the failing scenarios fail as well as the headline number.

Is 1,000 simulations enough?

For most personal planning, yes. Some tools, including Boldin's paid tier, run 1,000. Others, such as RetireSure Simulator, run 10,000. More runs give a smoother estimate, but the return assumptions, time horizon and spending inputs affect the result far more than the run count.

Is Monte Carlo analysis too optimistic or too pessimistic?

It depends on the model, and experts disagree. Fat-tail critics argue that bell-curve models underweight crashes. One Kitces Research analysis found that 6.5% of Monte Carlo scenarios were worse than the worst historical case, which suggests it can be harsher than history. Either way, test your plan by changing the inputs rather than relying on a single number.

Do I need to link my bank accounts to use retirement simulation software?

Not always. Some tools require linked accounts and others work from a few typed-in numbers. Monte Climb gives an answer from three inputs (age, retirement savings and monthly spending), runs in your browser, and saves nothing until you choose to.