The dataset was partitioned into three groups (Figure ). The first was an external validation set that was left out until model building and selection were complete. This set included 17 data points (black boxes in Figure , black stars in Figure ), representing each substrate once and each catalyst once or twice. Of the remaining 153 data points, a Kennard Stone algorithm was used to define 50% as the training set (solid gray circles, Figure ) and the other 50% as the test set (teal crosses, Figure ). Forward-stepwise linear regression was employed to build models for the observed selectivity (ΔΔG ‡ ) using DFTderived molecular descriptors of both the catalyst and the substrate. Molecular mechanics conformational searches were used to generate conformer ensembles for both the substrates and catalysts. After geometry optimization, each conformer's steric and electronic properties were collected to determine ensemble-dependent descriptors capturing molecular flexibility (see SI for details). The resultant models built from these descriptors were parsed based on their cross-validation and testset statistical measures. Averaged leave-one-substrate-out and leave-one-catalyst-out mean absolute error (MAE) values were used as an additional validation technique to ensure the model was not heavily biased to specific substrates or catalysts. The presented model (Figure ) was selected to allow the descriptors and their coefficients to be interpreted to provide insight into the reaction mechanism; however, numerous models with similar statistics (presented in the SI) were determined. Averaged leave-one-substrate-out (0.224 kcal/mol) and leaveone-catalyst-out (0.223 kcal/mol) MAEs for this model indicate that in generalizing to the complete sampling of the substrate and catalyst members (training MAE = 0.185 kcal/mol), some precision is sacrificed. However, the external validation set was predicted similarly to the test set (test MAE = 0.177 kcal/mol, external validation MAE = 0.183 kcal/mol), demonstrating the model can predict reactions of unseen substrate-catalyst combinations.