The enantioselective oxidation of C(sp )-H bonds converts readily available and simple organic frameworks into high added-value and chemically versatile enantiomerically enriched oxygenated compounds. Notwithstanding, site-and enantioselective C-H oxidation reactions are challenging transformations due to the presence of numerous aliphatic C-H bonds in organic molecules and their intrinsic low reactivity that generally require highly reactive reagents operating via paths seldom compatible with asymmetric catalysis. These challenges render enantioselective C-H oxidation functionally limited to enzymatic systems and few synthetic catalysts that operate in substrates containing activated (benzylic or 𝛼-to-heteroatom ) C(sp )-H bonds. In this context, the most promising candidates to develop enantioselective C-H oxidation reactions are iron and manganese complexes containing tetradentate ligands due to their ability to oxidize strong C-H bonds in a stereospecific manner. Traditional optimization protocols in stereoselective oxidation reactions often mimic aspects of high-throughput experimentation (HTE) techniques, a resource-intensive and time-consuming method. In this regard, systematic modification of the properties of the species involved in the system can be regarded as an alternative strategy for reaction optimization which-using a simple trial and error approach-has found use in asymmetric epoxidation and C-H oxidation reactions developed with this type of catalysts. While in some instances satisfactory performance has been achieved from these approaches, limited mechanistic information regarding the factors controlling the activity and selectivity has been attained. Identification of these factors has allowed some degree of predictability in the site selectivity of C-H oxidation reactions, an aspect that represents a paradigm shift in the standard logic of organic synthesis. In this context, statistical modeling tools can afford mechanistic interpretability and simultaneously identify better performances from collected datasets.