Monte Carlo Simulation is a statistical technique used to understand the impact of risk and uncertainty in prediction and forecasting models. It works by running many simulations, each time using random inputs to see how they affect the outcome. This method helps in estimating probabilities and making informed decisions in fields like finance, engineering, and project management. By generating a large number of possible scenarios, Monte Carlo Simulation provides a range of possible outcomes rather than a single result. This allows analysts to visualize risks and make better choices based on the likelihood of different events occurring, ultimately leading to more robust planning.