To gain a deeper understanding of separation processes within nanoporous materials, a machine learning prediction of Xe/Kr ambient-pressure selectivity was performed, aiming for faster results compared to standard GCMC calculations. The CoRE MOF 2019 database was utilized for MOF structures, enabling the evaluation of xenon/krypton selectivity in less than a minute, whereas an equivalent GCMC calculation typically requires approximately 40 min.