Analyzing results before BAC application reveals substantial accuracy variability across functionals, even at identical basis sets. Without BACs, more advanced functionals such as M06-2X and ωB97X-D typically outperform simpler ones like B97-1 (Table ). Once BACs are applied, however, these variations narrow considerably, indicating that systematic DFT errors can be largely mitigated by bond-additivity corrections. Notably, B97-1, a relatively simple hybrid GGA, achieves accuracy comparable to more sophisticated functionals like M06-2X (hybrid meta-GGA) and ωB97X-D (range-separated hybrid GGA with dispersion) when BACs are used, despite its lower theoretical hierarchy and cost. This ability of BACs to reduce sensitivity to functional choice extends to basis-set selection as well. Before BAC application, expensive functionals like DSD-PBEP86-D2 benefit more from increasing basis-set size than simpler ones such as B97-1 (Figure ). However, once BACs are applied, both methods experience notable improvements, and accuracy variations across basis sets, particularly beyond def2-SVP, are substantially reduced. In fact, B97-1 can then achieve accuracy closer to DSD-PBEP86-D2, despite being substantially more cost-effective. Moreover, while moving to larger basis sets does continue to boost accuracy, it also yields diminishing returns beyond def2-TZVPD, making this basis set an optimal balance for most applications. Nevertheless, even the best single-step DFT methods cannot entirely match the accuracy delivered by the previously mentioned DLPNO//DFT composite approaches, demonstrating that composite methods retain a performance edge in highaccuracy thermochemistry.