We expect that future work on computational modeling of Mnporphyrin-catalyzed fluorination, based on intelligent reconstruction of transition states for the limiting stage of the catalytic cycle, and quantum chemical simulations of properties of these transition states, will be able to guide substrate-specific optimization of the reaction conditions, including the catalyst optimization, and predict regioselectivity of functionalization of a given substrate under given conditions. The ab initio character of such models would allow for better extrapolations to new substrates. A combination of computational modeling and experimental studies is also highly desirable. Overall, Mnporphyrin-catalyzed fluorination of organic substrates is a promising, but still problematic technique, and its improvements may be guided by computational modeling of transitions states in these reactions.