Money Tools & AdvisorsIntermediate5 min read

Monte Carlo retirement projections explained

That '87% success rate' your planning tool shows isn't a guarantee or a grade — it's a probability from thousands of simulated markets. Here's how to read it.

Open a modern retirement tool and you'll likely see a result like 'Your plan has an 87% probability of success.' It looks precise and slightly ominous. Understanding where that number comes from — and what it does and doesn't promise — turns it from a mysterious verdict into a genuinely useful planning signal.

What a Monte Carlo simulation does

Instead of assuming your investments earn the same return every year, a Monte Carlo simulation runs your plan through hundreds or thousands of possible market futures — some with roaring bull markets, some with brutal crashes early in retirement, some middling. In each run it checks whether your money lasted through your planned lifespan. The 'success rate' is simply the percentage of those simulated futures in which you didn't run out of money. An 87% result means that in 87% of the modeled scenarios, the plan held.

Why it beats a single-number projection

It captures sequence-of-returns risk — the danger that a crash right after you retire does far more damage than the same crash later.
It shows a range of outcomes instead of one falsely precise figure.
It reframes planning around probability and resilience rather than a single 'you'll have exactly $X' fantasy.

What counts as 'good enough'?

There's no universal pass mark, but many planners treat something in the range of roughly 80–90% as a reasonable target for a flexible retiree — high enough to be secure, without requiring you to work years longer to chase an illusory 99%. The right number depends on how much you could cut spending in a bad stretch; a flexible retiree can safely aim lower than someone with rigid, non-negotiable expenses.

The traps in the number

Trap	Why it matters
Garbage-in assumptions	Optimistic return/inflation inputs inflate the success rate
False precision	'87.3%' implies accuracy the model can't have
Ignoring flexibility	Real retirees cut spending in bad years; the model may assume they don't
Chasing 100%	Requires massive over-saving or working far longer for tiny risk reduction
One-and-done	Markets and life change — it needs re-running

How a success rate can mislead

Using the number wisely

1
Check the assumptions behind it
A 95% success rate built on a 10% return assumption is weaker than an 85% built on conservative inputs. Look under the hood.
2
Think in terms of flexibility, not perfection
Ask 'if I hit a bad decade, could I trim spending?' A flexible plan can accept a lower success rate safely.
3
Re-run annually and after big changes
Treat it as a dashboard gauge you glance at, not a one-time diagnosis.
4
Pair it with guardrails
Combine the probability with a spending rule — trimming withdrawals in down years dramatically raises real-world success.

The bottom line

A Monte Carlo success rate is a probability drawn from thousands of simulated markets, not a promise or a grade. Read it alongside its assumptions, aim for a sensible range rather than a perfect 100%, lean on your ability to adjust spending, and re-run it over time. It's one of the best planning tools available — as long as you remember it models the future rather than knowing it. This is educational information, not individualized advice; a qualified planner can build and interpret projections for your situation.

Check your understanding

1 of 3

Your tool shows an '87% probability of success.' What does that actually mean, per the article?

Not quite — try again.

The Worth letter

Get smarter about money every week

One email, no spam — practical guides and Worth updates. Unsubscribe anytime.

Put this into practice

Worth tracks your accounts, budgets, and goals — so the concepts in this article aren't just theory.

Start free trial