Bayes’ Theorem postulates that the probability of a hypothesis being true increases or decreases as pieces of evidence for or against it accumulate. In the words of Bennett (2009: 8), ‘the more unlikely a piece of evidence [E] is in light of alternatives to explanation H, the more that evidence [E] increases our confidence that H is true . . .’ Although it remains controversial whether it makes sense to assign specific numerical probabilities to qualitative evidence (Beach, 2017: 15; Fairfield and Charman, 2017; Zaks, 2021), applying the general principles of Bayesian inference can be considered another benchmark for process-tracing research.