Low retention rates in higher education Information Technology (IT) studies have led to an unmet demand for IT specialists. Therefore, universities need to apply interventions to increase retention rates and provide the labor market with more IT graduates. However, students with different characteristics may need different types of interventions. The current study applies a person-oriented approach and identifies the profiles of first-year IT students in order to design group-specific support. Tinto's integration model was used as a framework to analyze questionnaire data from 509 first-year IT students in Estonia. The students' response profiles were distinguished through latent profile analysis, and the students were divided into four profiles based on their responses to questions about academic integration, professional integration, and graduation-related self-efficacy. The difference in academic integration was smaller among the profiles than the difference in professional integration. Knowing these profiles helps universities to design interventions for each student group and apply the interventions to increase the number of IT graduates.