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Although the genus Rhododendron is globally distributed and rich in bioactive constituents, the metabolomic landscapes of most species remain unexplored, hampering elucidation of their adaptive strategies and pharmaceutical potential. Objectives: This study sought to construct comprehensive metabolic atlases of four representative yet understudied Rhododendron species—R. triflorum, R. faucium, R. nivale, and R. strigillosum—and to quantify inter-specific metabolic divergence by UPLC-MS/MS-based, widely targeted metabolomics. Methods: The petals of four Rhododendron species were freeze-dried, pulverised, and extracted with 70% methanol (containing an internal standard). Metabolites were separated on an SB-C18 column (2.1 × 100 mm, 1.8 µm) using a 0–95% acetonitrile gradient (flow rate 0.35 mL min−1, 40 °C) and analysed by tandem mass spectrometry. Reliable quantification was ensured by molecular weight database matching, ion source standardisation, and quality control (QC), achieving a coefficient of variation (CV) < 15%. Principal component analysis (PCA) and optimised partial least squares discriminant analysis (OPLS-DA) were performed on standardised data with unit variance. Results: A total of 3705 metabolites were confidently identified, dominated by flavonoids (870), terpenoids (572), phenolic acids (394), and amino-acid derivatives (332). PCA and OPLS-DA models revealed clear species-specific clustering (R2Y ≥ 0.98, Q2 ≥ 0.95; permutation test p < 0.01). Comparative analysis yielded 1495 significantly differential metabolites; R. triflorum exhibited the highest cumulative abundance, followed by R. faucium, R. nivale, and R. strigillosum. KEGG enrichment highlighted “metabolic pathways” as the most significantly over-represented, together with flavonoid biosynthesis, phenylpropanoid metabolism, and terpenoid backbone biosynthesis. Conclusions: The study delivers the first high-coverage metabolomic reference for four neglected Rhododendron species, evidencing profound inter-specific metabolic differentiation centred on flavonoids, terpenoids, and phenolic acids. The data provide a robust foundation for understanding molecular adaptation to alpine environments and for accelerating targeted drug discovery from Rhododendron resources.