Mediation analysis uncovers the process by which a predictor affects an outcome through one or more intermediate variables. This chapter introduces the traditional approach to mediation, focusing on path analysis, the Baron & Kenny framework, and the Sobel test. Practical limitations of this approach are discussed, especially in the presence of confounding. Then, it presents a modern causal inference framework for mediation, including counterfactual definitions of direct and indirect effects. The use of bootstrapping is demonstrated with business examples. Assumptions such as sequential ignorability are explored in detail. Graphical representations, including path diagrams and causal graphs, are used to aid interpretation. This chapter provides the tools to not only estimate mediation effects but also to assess their robustness, interpret their business relevance, and report them transparently.