Health inequalities in Europe are often examined using unidimensional socioeconomic variables, which can mask heterogeneity within minoritized populations. This study applies Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to examine how minority group, gender, age, and education jointly pattern self-rated health among migrants and native-born ethnic minorities in 28 European Union countries.We included 22,611 participants from the European Union Minorities and Discrimination Survey (EU-MIDIS II, 2016). The sample comprised immigrants from North Africa, Sub-Saharan Africa, South Asia, Turkey, and other parts of Asia; recent migrants; and two native-born minority groups (Roma and individuals of Russian background). We analyzed 64 strata defined by minority groups, age, gender, and education, with country random intercepts. Using multilevel logistic and linear models for self-rated health, we quantified general contextual effects (VPC), specific contextual effects, and discriminatory accuracy (AUC).The results reveal a multidimensional social gradient in self-rated health. Roma and individuals of Russian background reported the poorest health outcomes, while Asian and recent migrant groups had comparatively favourable profiles. A substantial portion of the total variability in self-rated health is structured by intersectional strata, indicating that health inequity among minoritized groups in Europe is not reducible to the independent contribution of each social dimension but reflects the convergence of ethnicity, sex, age, and socioeconomic position.These results show substantial heterogeneity within and between minoritized groups in Europe. Effective public health responses require intersectional policy frameworks that move beyond single-axis approaches to address the structural drivers of health inequity.