Top 10 Best Monte Carlo Simulation Software of 2026

@RISK by Lumivero is a leading Monte Carlo simulation software that integrates seamlessly as an add-in for Microsoft Excel, enabling users to model uncertainty by replacing fixed values with probability distributions. It performs thousands of simulation iterations to generate probabilistic outputs, including histograms, cumulative distributions, tornado charts, and sensitivity analyses. Widely used in finance, engineering, oil & gas, and project management, it supports correlations, optimizations, and advanced risk metrics for comprehensive uncertainty quantification.

Oracle Crystal Ball is a powerful Excel add-in designed for Monte Carlo simulation and risk analysis, allowing users to model uncertainty by replacing static spreadsheet values with probability distributions. It runs thousands of simulations to generate probabilistic forecasts, sensitivity analyses via tornado charts, and correlation modeling. Additionally, it includes OptQuest for optimization and advanced tools for data fitting and scenario analysis, making it ideal for complex forecasting in spreadsheets.

ModelRisk, from Vose Software, is a powerful Excel add-in designed for Monte Carlo simulation and quantitative risk analysis, enabling users to model uncertainty directly in spreadsheets. It offers an extensive library of over 1,000 probability distributions, advanced correlation techniques including copulas, and tools for sensitivity analysis, optimization, and scenario planning. The software excels in turning deterministic Excel models into probabilistic ones, providing detailed risk insights through tornado charts, heatmaps, and simulation dashboards.

Analytic Solver Platform is a powerful Excel-based software suite from Frontline Systems that excels in optimization, simulation, and predictive analytics. For Monte Carlo simulation, it enables users to perform risk analysis by defining uncertain variables, running thousands of iterations, and generating distribution outputs like tornado charts and statistics. It stands out by combining simulation with advanced optimization solvers for stochastic programming and decision optimization under uncertainty.

GoldSim is a dynamic simulation software platform designed for modeling complex systems with time-varying processes, feedback loops, and uncertainties using Monte Carlo methods. It allows users to build visual, hierarchical models that propagate uncertainties through probabilistic simulations, sensitivity analysis, and risk assessments. Primarily used in engineering, environmental science, and project management, it excels at handling real-world systems where discrete events, continuous processes, and decision logic intersect.

Simul8 is a discrete event simulation software that excels in modeling complex processes with built-in Monte Carlo simulation capabilities for handling uncertainty and risk analysis through probabilistic inputs and multiple iteration runs. It offers a visual drag-and-drop interface to build, animate, and optimize models across industries like manufacturing, healthcare, and logistics. Users can define distributions for variables, run scenarios, and generate statistical outputs for decision-making under variability.

AnyLogic is a multimethod simulation modeling software that supports agent-based, discrete event, and system dynamics approaches, with strong capabilities for Monte Carlo simulations via its experimentation framework. It enables users to perform thousands of model runs with randomized inputs from probability distributions to analyze uncertainty and risk in complex systems. While powerful for integrating Monte Carlo into broader simulations, it is more suited to advanced modeling than simple spreadsheet-based Monte Carlo analysis.

Arena, developed by Rockwell Automation, is a powerful discrete event simulation software primarily used for modeling complex manufacturing, logistics, and business processes. It incorporates Monte Carlo simulation methods through its Process Analyzer and OptQuest modules to handle variability, risk analysis, and optimization under uncertainty. Ideal for industrial applications, it allows users to visualize system performance, identify bottlenecks, and test scenarios with probabilistic inputs.

MATLAB, developed by MathWorks, is a high-level programming language and interactive environment for numerical computation, data analysis, and visualization. For Monte Carlo simulations, it leverages built-in functions for random number generation, statistical distributions, and sampling via the Statistics and Machine Learning Toolbox. It supports parallel and GPU computing to accelerate large-scale simulations, integrating seamlessly with visualization tools for result analysis and reporting.

FlexSim is a comprehensive 3D discrete event simulation software primarily used for modeling manufacturing, logistics, and healthcare processes. It incorporates Monte Carlo simulation capabilities through its Experimenter tool, allowing users to run multiple replications with probabilistic distributions for uncertainty analysis. While powerful for complex system simulations, it is less optimized for pure statistical Monte Carlo compared to dedicated tools.