Context <p>Density functional theory (DFT) remains a central tool in thermochemical modeling, yet its predictive reliability is strongly system-dependent and often obscured by global statistical metrics. In this work, a diagnostic analysis of the B3LYP functional is presented to identify the dominant physical origins of systematic thermochemical errors. Rather than introducing new calculations, previously published benchmark datasets are reorganized within a unified, semi-quantitative diagnostic framework that links molecular descriptors to characteristic error mechanisms. The analysis reveals distinct failure modes associated with molecular size, structural compactness, dispersion-dominated interactions, and electron density localization. Linear hydrocarbons exhibit cumulative size-dependent errors consistent with missing medium-range correlation effects, while branching-sensitive isomerizations show pronounced overstabilization of linear structures that is significantly—but not fully—reduced by dispersion corrections. In contrast, heteroatom-containing systems display strong sensitivity to diffuse basis functions, indicating that density localization and polarization effects dominate over dispersion. Comparative analysis further shows that polarization and dispersion corrections provide only moderate improvements in these systems relative to diffuse functions. These results demonstrate that B3LYP accuracy cannot be uniformly improved by a single correction strategy and must instead be interpreted within a system-specific, physically informed framework.</p> Methods <p>The analysis is based on previously published thermochemical benchmark datasets comprising neutral closed-shell organic molecules and representative isomerization reactions. Electronic structure methods considered include Hartree–Fock (HF), B3LYP with the 6—31G(d), 6—31G(d,p), and 6—31 + G(d,p) basis sets, dispersion-corrected B3LYP variants, and the semiempirical PDDG/PM3 Hamiltonian. No new quantum chemical calculations were performed; instead, published heats of formation and isomerization energies were systematically reorganized and evaluated using mean absolute errors (MAEs) and structure-dependent diagnostic classifications to identify reproducible performance trends.</p>