A LightGBM classifier and a LightGMB regressor are trained on the entire dataset (740 compounds; 3278 hydricities) of QM computed hydricities to assess the generalization capability of our ML models. An out-of-sample dataset with 222 reactions (1749 sites) from the literature is used for this. The reaction dataset contains reactions suspected to involve a protonation step, and we speculate that the C-H site with the lowest hydricity is most likely the site of the reaction, as we see from the section. To get a better overview of the reaction dataset, we also compute QM hydricities for these reactions and compare them against the ML models. A summary of the performance metrics for the reaction dataset is found in Table , and more details are found in Tables and.