To provide more nuanced guidance for method selection, we evaluated sixteen recommended model chemistries across six molecular categories: cations, anions, zwitterions, neutral singlets, doublets, and triplets (Figure ). In general, BAC effectiveness strongly depends on molecular type. For neutral singlets, which dominate our training set, BACs consistently enhance accuracy for all tested QM methods. Similarly, anions and zwitterions benefit from BAC application, although they often exhibit larger residual errors overall. Triplets, by contrast, sometimes show increased errors upon BAC correction (e.g., B3LYP/def2-TZVPD), presumably due to limited representation of triplets (n = 7) in the training data. Overall, these results demonstrate that BACs can effectively handle diverse species but may be less beneficial for those significantly underrepresented in the training set, such as triplets. The findings underscore the importance of matching geometry optimization and single-point level of theory to the target species class, and highlight that further improvements, especially for species with unusual electronic states, may require either specialized corrections or expanded high-accuracy reference data.