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Background: Research on the health effects of chemical mixtures has focused mainly on early life rather than adolescence, a potentially important developmental life stage. OBJECTIVES: We examined associations of a metal mixture with general cognition in a cross-sectional study of adolescents residing near ferromanganese industry, a source of airborne metals emissions. Methods: We measured manganese (Mn), lead (Pb), copper (Cu), and chromium (Cr) in hair, blood, urine, nails, and saliva from 635 Italian adolescents 10-14 years of age. Full-scale, verbal, and performance intelligence quotient (FSIQ, VIQ, PIQ) scores were assessed using the Wechsler Intelligence Scale for Children-III. Multivariable linear regression and Bayesian kernel machine regression (BKMR) were used to estimate associations of the metal mixture with IQ. In secondary analyses, we used BKMR's hierarchical variable selection option to inform biomarker selection for Mn, Cu, and Cr. Results: Median metal concentrations were as follows: hair Mn, 0.08 [micro]g/g; hair Cu, 9.6 [micro]g/g; hair Cr, 0.05 [micro]g/g; and blood Pb, 1.3 [micro]g/dL. Adjusted models revealed an inverted U-shaped association between hair Cu and VIQ, consistent with Cu as an essential nutrient that is neurotoxic in excess. At low levels of hair Cu (10th percentile, 5.4 [micro]g/g), higher concentrations (90th percentiles) of the mixture of Mn, Pb, and Cr (0.3 [micro]g/g, 2.6 [micro]g/dL, and 0.1 [micro]g/g, respectively) were associated with a 2.9 (95% CI: -5.2, -0.5)-point decrease in VIQ score, compared with median concentrations of the mixture. There was suggestive evidence of interaction between Mn and Cu. In secondary analyses, saliva Mn, hair Cu, and saliva Cr were selected as the biomarkers most strongly associated with VIQ score. Discussion: Higher adolescent levels of Mn, Pb, and Cr were associated with lower IQ scores, especially at low Cu levels. Findings also support further investigation into Cu as both beneficial and toxic for neurobehavioral outcomes. https://doi.org/10.1289/EHP6803, Introduction Recent progress in understanding how chemical mixtures affect health can be largely attributed to collaboration between scientific fields, innovation of statistical methods, and prioritization from funding agencies (Carlin et [...]