Generalized Additive Models (GAMs) are a type of statistical model that helps predict outcomes by looking at how different factors interact. Instead of assuming a specific relationship between variables, GAMs use flexible functions to capture complex patterns in the data. This approach allows for more accurate predictions and a better understanding of the underlying relationships between variables.