Beyond Side-Specific Distributions: Patient-Level Bilateral Agreement of Mandibular Third-Molar Classifications

Background/Objectives: The right and left mandibular third molars of the same patient may be expected to have similar radiographic characteristics. This study aimed to determine whether side-specific distributions of mandibular third-molar classifications correspond to patient-level bilateral agreement and whether identical Pederson scores may conceal differences in their underlying radiographic components. Methods: This retrospective cross-sectional study included 800 mandibular third molars from 400 patients with bilateral mandibular third molars. Panoramic radiographs were evaluated separately for each side using the Winter classification, Pell–Gregory classification, and Pederson difficulty index. Bilateral agreement was assessed using raw agreement, Cohen’s kappa, and weighted kappa coefficients, while side-specific distributions were compared using marginal homogeneity tests. Results: Raw agreement was 59.75% for Winter angulation, 56.0% for the combined Pell–Gregory classification, 69.5% for the Pederson difficulty group, and 48.75% for the total Pederson score. Kappa values were 0.42, 0.44, and 0.43 for Winter angulation, the combined Pell–Gregory classification, and the Pederson difficulty group, respectively. Complete agreement across all three systems was observed in 170 patients (42.5%). The Pell–Gregory ramus relationship showed substantial agreement (κ = 0.64), whereas depth showed moderate agreement (κ = 0.41). Left-side Pederson scores were significantly higher than right-side scores (p = 0.013), although the mean difference was only 0.15 points. Conclusions: Bilateral mandibular third molars showed only moderate patient-level agreement. Similarity in category distributions at the sample level should not be interpreted as within-patient agreement, and identical Pederson scores may conceal differences in angulation and position. Each mandibular third molar should therefore be evaluated separately, particularly in cases close to classification thresholds.