Organic photoredox catalysts enable diverse chemical transformations, but predicting their activity is challenging due to complex properties. Now, a two-step data-driven approach is introduced for targeted organic photoredox catalysts synthesis and reaction optimization. Using Bayesian optimization, promising catalysts can be efficiently identified, yielding competitive results with iridium catalysts.