This study examines how applicant profiles, prior experiences, and motiva-tion relate to admission decisions and early study persistence in informatics programs at Tallinn University of Technology (TalTech), Estonia (2020–2025). Drawing on Tinto’s integration model, Person–Environment Fit theo-ry, and Social Cognitive Career Theory, it analyzes how technical prepared-ness, institutional engagement, and self-efficacy shape enrollment and drop-out. The study combines qualitative content analysis of 168 applicant portfo-lios (2023–2025) with institutional enrollment and dropout data from 2020–2025, coding portfolios across five domains, including IT preparedness, en-gagement with TalTech, and extracurricular activities. Results show that prior engagement with the university, systematic IT experience, and bal-anced profiles combining technical and interpersonal competencies are the strongest predictors of both acceptance and persistence. The introduction of portfolio-based admissions was associated with reduced dropout by improv-ing alignment between applicants’ capabilities, motivations, and program expectations. At the same time, limited technical preparation and weak self-regulation increased the risk of withdrawal. Overall, the findings indicate that content-focused admissions can serve as an anti-dropout mechanism, with implications for equitable, data-informed admissions design in compu-ting education.