Mediation analysis in Single Case Experimental Designs (SCEDs) evaluates intervention mechanisms for individuals. Despite recent methodological developments, no clear guidelines exist for maximizing power to detect the indirect effect in SCEDs. This study compares frequentist and Bayesian methods, determining (1) minimum required sample size to detect indirect effects in AB designs, (2) relative power for proximal vs. distal mediators, and (3) optimal observation allocation between baseline and treatment phases. Simulation study results suggest highest power for proximal mediators with at least 60 observations evenly allocated to A and B phases. Findings from this study have important implications for the design and statistical analysis in numerous fields that routinely employ SCEDs, ranging from education to psychology and nursing.