Miniature artificial enzymes such as mimochromes provide a simplified platform to extract design principles for engineering rate enhancements beyond that of natural enzymes, although design optimizations have largely focused on geometric properties, leaving the impact of the electronic environment unexplored. To investigate how the electronic environment influences reactivity, we carry out classical and ab initio molecular dynamics (MD) simulations, supervised machine learning (ML), and statistical analysis of a series of mimochromes, MC6, MC6*, and MC6*a. Our classical MD simulations reveal a correlation between increased protein–heme contact and improved reactivity, confirming the importance of geometry, while ab initio MD simulations provide insight into the electronic environment, showing the electrostatic potential (ESP) at the metal center also correlates with reactivity. Quantum mechanical calculations of sulfoxidation and hydroxylation reactions demonstrate that the negative ESP at the metal center and active site electric field stabilize the highest-energy intermediate. Furthermore, using ML classifiers, we identify critical residues such as Lys12 and Asp18 in MC6*a that demonstrate charge-coupling patterns that explain differences in reactivity. This suggests that the reactivity series in mimochromes is primarily driven by key aspects of partial charge distribution dynamics, which should guide the engineering of next-generation metalloenzymes.