Investigating kinetic mechanisms to design efficient photocatalysts is critical for improving photocatalytic CO₂ reduction, but the stochastic photo-physical/chemical properties of kinetics remain unclear. Herein, we propose a statistical study to discuss the stochastic feature evolution of photocatalytic systems. The uncertainties of light absorption, charge carrier migration, and surface reaction are described by nonparametric estimation methods in the proposed model, which includes the effect of operational and material parameters. The density distribution of surface electrons shifts from a skewed distribution to an approximate uniform distribution as incident photon density increases. The system temperature rising induces the rate-determining step of surface reactions to change from charge carrier kinetics to reactant activation processes. Benefiting from the synergistic optimization between the operational parameter and active site density, the electron-capturing probability of active sites is boosted from 0.06 to 0.17. The modified reaction kinetic equation is constructed based on the distribution function of charge carrier kinetics. Furthermore, the experimental photoactivity results are consistent with the statistical analysis, which proves the feasibility of the established model. The characterization tests show that the gap between testing activities and theoretical efficiency is caused by a mismatch between charge carrier supply and mass transfer. Our work unveils the stochastic features in photocatalytic CO₂ reduction, offering a comprehensive analytical framework for photocatalytic system optimization.