Notably, a model trained on Mordred descriptors and the device architecture subset of features (Figure ) is not significantly better than the same model trained on only Mordred descriptors, which achieves a R 2 score of 0.6±0.03 (Figure ). This suggests that the models' performance is limited by the quality of the underlying data. Finally, we evaluated the performance of the HGB model when including features related to charge carrier mobility: log(hole mobility) and log(electron mobility) from space charge-limited current (SCLC) diode measurements, as well as the ratio of the two. The resulting model performance is significantly better (R 2 = 0.68±0.02, Figure ) than anything else reported in the literature. However, including these values does not make a lot of sense from a practical perspective. In order to predict the PCE of a device, one would already need to have measured the hole and electron mobilities. This involves fabricating a device with a modified electrode architecture, and is therefore less efficient than simply measuring the device's performance experimentally.