Case-based approaches to studying public policy have the goal of learning about how policy processes actually operate within real world cases. In a case-based approach, the analytical priority is the in-depth study of operative processes within a case. Comparisons act as an adjunct method used to map populations into smaller, relatively homogeneous subsets that enable us to select relevant cases for within-case analysis. The upside of using case-based approaches to study public policy is that we learn a lot about how a policy intervention works in a given context, and the conditions required for it to work in a particular way. The downside is that our knowledge claims are relatively context-specific. Given that the core analysis is within-case, a core challenge in policy studies is assessing whether similar processes are operative in multiple cases. The crux of the challenge is that studying how policy processes play out within cases requires that we significantly lower the level of abstraction of our analysis. However, this means that our findings about how processes play out in particular cases become highly sensitive to contextual differences across cases, meaning that it can be difficult to make meaningful generalizations about how policy processes actually work that hold for cases in different contexts. This chapter uncovers the fundamental ontological and epistemological assumptions that distinguish case-based from variance-based approaches. It presents how case-based methods that combine the comparative mapping of a set of cases and the in-depth tracing of mechanisms (i.e. processes) within multiple cases in this bounded population enable valid causal inferences to be made about policy processes operative within cases that share a set of contextual conditions (aka scope conditions).