This chapter compares process tracing with qualitative causal inference to clarify their methodological domains, overlaps, and divergences. Process tracing, rooted in the detective model of inference, is shown to be a valid reasoning strategy within its epistemic domain – situations where background knowledge permits the substitution of a bias-free causal graph for a bias-saturated one. However, outside this narrow domain, particularly in the social sciences, process tracing is prone to false positives because it assumes away potential bias. The chapter surveys four variants of process tracing: orthodox, Bayesian, sequential, and mechanistic. While each represents an important development, all share a vulnerability to unacknowledged systematic error when applied to causal inference. Examples from published research illustrate how even methodologically rigorous applications of process tracing may inadvertently generate false positives. By contrast, qualitative causal inference was designed to address this problem by explicitly testing for causal continuity along the front-door path and causal discontinuity along bias-inducing paths. The chapter concludes by weighing the relative strengths of the two approaches. While process tracing remains useful in domains where causal structures are well understood, qualitative causal inference offers a more robust framework for within-case causal analysis in the complex and uncertain settings typical of social science research.