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FIRE Calculator

Estimate years to financial independence across lean/regular/fat targets with deterministic Monte Carlo success scoring.

FIRE Inputs

Model lean, regular, and fat-FIRE paths with volatility-aware success probability.

FIRE Horizon

Years to FI
26 years
Monte Carlo success
98.25%

FI age: Age 60

FIRE Target Levels

Lean, regular, and fat spending envelopes

Lean target
$1,040,000.00
Regular target
$1,300,000.00
Fat target
$1,625,000.00

Portfolio vs FI Requirement

When projected portfolio catches required portfolio

Age 34Age 48Age 69
Projected portfolio
$5,239,469.75
Required portfolio
$3,085,166.74

FI Timing Variants

How spending level shifts timeline

Lean FI
22 years
Regular FI
26 years
Fat FI
30 years

US usage

Search intent is strongest around planning precision, transparency, and scenario comparison.

EU usage

Users typically compare conservative vs optimistic assumptions before committing to a decision.

APAC usage

Scenario speed and mobile readability matter for quick, repeated recalculation workflows.

How To Use This Calculator

  1. Enter current portfolio, annual spending, and yearly savings contributions.
  2. Set return, volatility, inflation, and withdrawal-rate assumptions.
  3. Review lean, regular, and fat FIRE targets in one view.
  4. Check timeline and Monte Carlo success probability for plan robustness.
  5. Adjust savings or spending to see how quickly FI timing changes.
  6. Save a shareable link with your assumptions, then run one conservative and one optimistic scenario before deciding.
For AI Agents (Optional)

Human mode is default. You can ignore this section unless you use AI agents or structured automation.

Agent Contract

Contract: fire_calculator v1 

{
  "tool": "fire_calculator",
  "current_age": 34,
  "current_portfolio": 180000,
  "annual_spending": 52000,
  "annual_savings": 24000,
  "expected_return_percent": 7,
  "volatility_percent": 14,
  "inflation_percent": 2.5,
  "withdrawal_rate_percent": 4,
  "horizon_years": 35
}

Frequently Asked Questions

What does Monte Carlo success represent?

It estimates the share of deterministic simulation paths that reach FI within your selected horizon.

Why are there lean and fat targets?

They provide lower and higher spending envelopes so you can compare lifestyle tradeoffs.

Can negative returns be modeled?

Yes. Volatility and return assumptions can produce down years in simulation paths.

Is this retirement advice?

No. This is a scenario-planning model and should be combined with professional guidance where needed.

Can agents automate this?

Yes. fire_calculator has a deterministic contract and explicit assumption echo.

Is this tool free and private to use?

Yes. AI Fin Hub tools are free, no-signup browser tools. Inputs stay in your browser unless you choose to share a URL.

Can I use this with AI agents too?

Yes. Human mode is the default experience. If you use AI automation, open the optional 'For AI Agents' section for deterministic contracts.

Is this professional advice?

No. Outputs are planning estimates only — not financial, tax, or investment advice.

Planning estimates only — not financial, tax, or investment advice.