This calculator is designed as a tool for quantitatively estimating the number of potentially habitable, Earth-like planets in the Galaxy using the equation above. The methodology is based on a combination of empirical estimates of astrophysical parameters and free variables whose values reflect either scientifically grounded approximations or hypothetical assumptions (e.g., the proportion of complex life, arbitrary parameter fₓ). Input parameters are given as relative proportions (0–1) or absolute numbers; percentages are entered in decimal form (e.g., 27% → 0.27).
Deterministic approach. Selecting the Calculate Deterministic function triggers a linear multiplicative estimate, where all parameters are multiplied. The result is a point estimate of the number of habitable planets, rounded to a whole number.
Stochastic approach (Monte Carlo). The Run Monte Carlo Simulation function performs a user-specified number of iterations (≥1000). The values of individual parameters are sampled from normal distributions centered on the given input value with a small standard deviation, allowing for uncertainty. The model also includes a basic correlation dependency: larger planets have a higher probability of having a protective magnetic field.
Extrapolation (“Where are they?”). Based on the obtained estimates and the area of the Milky Way, the average expected distance to the nearest habitable planet is calculated, expressed in light-years. A 2D model (galactic disk area) is used, as the Milky Way is a thin disk structure with a thickness of about 1000 light-years compared to a diameter of about 100,000 light-years, which for the purpose of estimating distances to the nearest planet justifies a flat distribution approximation instead of a volumetric 3D model. For 2D disk model: where (surface density). For 3D disk model: where (disk volume density). For 3D spherical model: where (spherical volume density).
Output data: The simulation provides the average number of habitable planets along with a 95% confidence interval (CI) showing the probable range of outcomes. Two graphs are displayed: the distribution of individual simulation runs and a Gaussian curve showing probability versus number of planets.