Causal models are frameworks used to represent and analyze the cause-and-effect relationships between variables, providing a structured approach to understanding how changes in one variable can influence others. They are essential in fields like epidemiology, economics, and machine learning for making predictions and informed decisions based on causal inference rather than mere correlation.