Computational predictions of SCO behavior are carried out using ab initio methods such as density functional theory (DFT), but predictions are highly sensitive to the choice of density functional approximation (DFA) from a wide range of available functionals. DFT is widely employed for its relatively modest cost but suffers from self-interaction error or delocalization error and static correlation error. Prior work has demonstrated the barriers to highthroughput screening of SCO complexes with DFT, highlighting the challenges of identifying bestperforming functionals. For example, while hybrid functionals and DFT+U make suitable predictions of spin splitting energies, the former are computationally expensive and the latter makes structure and property predictions worse. Prior studies with DFT found B3LYP , B3LYP* (i.e., B3LYP with a Hartree-Fock (HF) admixture (aHF) of 0.15) , TPSSh , and B2PLYP to predict differences in HS and LS states of Fe(II) complexes accurately. Given that these studies are mostly small in scale and disagree on what functionals best predict SCO behavior, we recently studied 95 Fe(II) SCO complexes in a data set we curated called SCO-95 with over 28 DFAs to determine which functionals make the best predictions of SCO behavior on a larger data set. Although we identified B3LYP (aHF = 0.10), TPSSh, and M06-L to accurately predict the spin splitting Gibbs free energies, we showed they fail to predict the experimental T1/2 values we curated from the literature accurately.