To validate our QM workflow, we use a dataset of 35 experimental C-H hydricities in DMSO and MeCN (9 compounds) from Parker and coworkers . As 35 C-H hydricities are insufficient to train an ML model, we use the same QM dataset from our previous paper and combine it with the experimental dataset to calculate QM C-H hydricities. After removing compounds that failed the QM workflow (see next section), the total QM dataset consists of (740 compounds and 3278 hydricities) and is used to train ML models. Hereafter, a reaction dataset with 250 hydride transfer-like reactions from the literature (250 compounds, 2018 C-H sites) functions as an additional test set for the ML models and is compared with the QM workflow to quantify the predictability of the reaction site by using the lowest C-H hydricity. The reaction dataset consists of different reaction types: carbene insertion (58 compounds); H abstraction C-N (45 compounds); oxidation ; H abstraction C-X (29 compounds); Oxidative degradation ); H abstraction C-C ; miscellaneous .