The RF regressor model trained to predict CH4 working capacity demonstrates excellent performance for both the mechanically stable subset of USMOF DB and CoRE MOF 2019, achieving high accuracy (test R 2 = 0.99 and 0.97, respectively) and low mean absolute error (MAE) of test prediction (Supporting Information Figure ). The models predicting CO2 working capacity for both databases exhibited somewhat lower test R 2 values, 0.83 and 0.97 for USMOF DB and CoRE MOF 2019 DB, respectively, when compared to the models predicting CH4 working capacity (Supporting Information Figure ). The lower accuracy of the CO2 model trained on USMOF DB than that trained on CoRE MOF 2019 is due to the mechanically stable USMOF DB subset being both smaller (i.e., 1,102 for mechanically stable MOFs in the USMOF DB and 9,525 for CoRE MOF 2019) and having a much wider range of geometric properties (Supporting Information Figure ).