In order to facilitate the high-throughput generation of computed data by retrieving information from existing crystallographic data repositories, we here present ground state spin prediction models that will extend the capability of our cell2mol 22 software. cell2mol was built to offer a comprehensive interpretation of the unit cell by extracting the connectivity and total charge of molecules within a crystal structure, placing emphasis on transition metal-containing structures. Yet, information regarding another necessary input of quantum chemical computations, i.e., the molecular spin, was missing from the interpretation. Here, we propose a general approach to predict the ground state spin of TM complexes. The TM-GSspin dataset, comprising 2,032 mononuclear first row TM complexes and their computed ground state spins, was constructed starting from the 31k complexes extracted from the CSD with cell2mol. TM-GSspin is currently the largest dataset that encompasses a diverse range of metals, metal OS, coordination geometries, and first coordination sphere compositions, while also containing total charge and ground state spin information.