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Description: Background: There is converging and compelling evidence that mental disorders are more optimally conceptualized in a hierarchical framework that transcends traditional categorical boundaries. However, the majority of this evidence comes from studies that draw upon predominantly Caucasian populations. Whether the hierarchical conceptualization of mental disorders generalizes across racial-ethnic groups, including for African American (AA) youths, is unclear. This research is especially crucial in light of the observed racial-ethnic differences in the prevalence rates of several mental disorders. Methods: We tested multidimensional and bifactor models of 15 DSM-5 diagnoses and psychiatric traits in two groups, including AA (n=3,088) and European American (EA) (n=5,147) youths aged 8-21 from the Philadelphia Neurodevelopmental Cohort (PNC). We also conducted multigroup confirmatory factor analyses to test for factorial invariance between the best fitting AA and EA multidimensional and bifactor models. Results: In the multidimensional model tests, a three-factor model, specifying internalizing, externalizing, and thought dimensions, emerged as the best fitting model for AAs and EAs. In the bifactor model tests, a three-factor model (i.e., internalizing, externalizing, and thought dimensions) that also specified a general factor emerged as the optimal for both AAs and EAs. The general factor accounted for a significant proportion of the covariation between the secondary factors and the individual disorders and traits. Furthermore, both models were factorially invariant, indicating that there was no significant difference in the factor structure of mental disorders between AAs and EAs in PNC. Conclusions: This study provides evidence that the hierarchical factor structure of mental disorders may be racial-ethnically robust. This finding has implications for etiological and epidemiological studies focused on racial-ethnic subgroup comparisons, particularly with respect to identifying similarities and differences in prevalence rates or sociodemographic risk factors for mental disorders.