In common understanding, resilience enables students to withstand adverse conditions. Resilient students achieve moderate to good educational outcomes in spite of high risks. To foster academic resilience, a deep understanding of risk and resources, their interplay and moderating effects is essential. We aim to achieve this goal by using hidden (latent) Markov modelling (HMM) to (1) identify risk and resilience in the Progress in International Reading Literacy Study (PIRLS) sample for Germany 2016 and (2) reflect on the interdependences between these factors. Furthermore, special educational needs (SEN) are introduced as a variable for post hoc analysis. A four-class solution was established and factors favoring resilience could be identified. Post hoc analyses of class allocations show that students with SEN are less likely being allocated to classes with high socio-economic resources and above average academic achievements than students without SEN.