Probabilistic models are mathematical frameworks used to represent uncertain situations by incorporating randomness. They help predict outcomes by assigning probabilities to different events or states, allowing for a better understanding of complex systems. These models are widely used in fields like statistics, machine learning, and economics. In a probabilistic model, each possible outcome is associated with a likelihood, which can be derived from historical data or expert knowledge. This approach enables decision-makers to evaluate risks and make informed choices, as it accounts for variability and uncertainty in real-world scenarios.