Statistical modeling is a mathematical framework used to represent complex data relationships and make predictions based on observed data. It involves creating a model that captures the underlying patterns in the data, allowing researchers and analysts to draw insights and make informed decisions. Common techniques include regression analysis, time series analysis, and Bayesian inference. By applying statistical models, one can estimate the likelihood of future events, understand the impact of various factors, and test hypotheses. This approach is widely used in fields such as economics, healthcare, and social sciences, making it a vital tool for data-driven decision-making.