Monte Carlo Simulations are powerful computational methods that utilize random sampling to model and analyze complex systems and processes. By running numerous simulations with varied inputs, they estimate the probability distribution of possible outcomes. Widely used in risk assessment, optimization, and decision-making, these simulations help predict uncertainties and inform strategies based on probabilistic insights.