This study used a person-centered approach to explore mental health status and profiles among a sample of 2262 university students and how these profiles differ in sociodemographic, academic, and lifestyle traits. Results revealed that around half of participants reported high well-being and life satisfaction, while over a third exhibited positive screening for anxiety, depression, and psychological distress. A latent profile analysis identified four distinct mental health profiles aligned with a dual-factor model of mental health: (1) complete mental health (28.5%), with high well-being and life satisfaction and low psychopathology; (2) troubled (20.7%), with average mental health and distress; (3) vulnerable (31.3%), with very low positive mental health, high psychopathology, and distress; and (4) symptomatic but content (19.5%), with average well-being but high reported anxiety and depression. Multinominal regression revealed that male students in natural/technical sciences with high GPAs were less likely to belong to profiles with lower well-being and life satisfaction and higher distress, while poor/excessive sleep and more leisure time predicted membership in these profiles. Implications for the assessment, support, and policy on the well-being of university students are discussed.