The influence of different dimensions of students’ social background on their academic achievement has been well-documented. However, despite the extensive research in this area, quantitative research has barely addressed how different dimensions of social background intersect with each other. The intersectional perspective, originating from qualitative research, has not been sufficiently adopted in quantitative analysis yet, which can be partly explained by a lack of suitable methodology. The majority of studies using regression-based analysis account only for the additive effects of different dimensions of social inequalities. And even if it is possible to account for the intersectional multiplicative effect in the regression by adding interaction terms, it is still problematic to model complex multi-dimensional interactions. However, recently, a more suitable method for quantitative intersectional analysis has been developed, the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). The project analyses inequalities in school outcomes from the intersectional perspective using the MAIHDA approach. The aim of the project is to explore whether different dimensions of social inequalities intersectionally affect different school outcomes (such as grades, eligibility, subject choices) of Swedish compulsory school graduates. The analysis is based on register data from Swedish compulsory school graduates in 2015-2019 and focuses on the intersection of gender, immigration status, geographical location, attending public or private school, as well as parental immigration status, education, and income.