Here we demonstrate an approach that was developed to automate the DFT-level calculations of energies of the auto-generated reaction intermediates. These results were further used to generalize mechanistic knowledge of a class of reactions, and the developed models were used for in silico prediction of reactions outcomes. This approach was tested on the important for green chemistry class of C-H activation reactions. Whilst this study does not completely solve the problem of developing a robust chemical reaction, it offers an approach that is complementary to efforts of developing machine learning models for predicting reaction outcomes.