The trained random forest models predicted all target energies with a mean absolute error (MAE) of less than 1.2 kcal/mol and a mean absolute percentage error (MAPE) of less than 16% (Supporting Information Table and Figure ). Using R 2 as a figure of merit, the SAPT0 component dispersion, electrostatics, and exchange energies were predicted most accurately (R 2 values of 0.83, 0.73, and 0.75, respectively), while B3LYP-D3 and SAPT0 interaction energies were predicted less accurately (R 2 values of 0.47 and 0.59, respectively, Figure ). Nevertheless, the MAE of 0.51 kcal/mol for B3LYP-D3 and 0.69 kcal/mol for SAPT0 are still lower than the expected error of the underlying methods (Supporting Information Table ). All models underestimate the strongest interactions, likely due to the small dataset size and limited number of structures with these interaction strengths (Figure and Supporting Information Figure ).