This chapter explores the concept of causality in epidemiology, highlighting its central role in interpreting associations between exposures and health outcomes. It begins with the theoretical foundations of causality, followed by a detailed examination of Austin Bradford Hill’s criteria as a practical framework for causal inference. The sufficient-component cause model is introduced to illustrate the multifactorial nature of disease causation, while the equivalence model offers a novel graphical approach that integrates both risk and protective factors to estimate the likelihood of an outcome, such as disease development. Together, these concepts equip epidemiologists with essential tools to critically evaluate evidence and draw robust conclusions about cause-and-effect relationships in public health research.