The prevalence of mental distress is higher among university students, and mental health disturbances are expected to rise amid significant social crises such as war. First-year students who enrolled in university programs after higher education institutions reopened in the midst of ongoing armed conflict face greater mental distress as they adjust to university life and deal with the aftermath of war. Therefore, this study aimed to investigate the prevalence of depression, anxiety, and stress and the predictive roles of social support and dysfunctional attitudes to determine the level of mental distress among students. A cross-sectional survey study was conducted among 335 first-year students at the University of Gondar. A multistage sampling technique was used to enroll participants. Data were collected using the depression, anxiety, and stress scale (DASS-21), the short version of the dysfunctional attitude scale, and the multidimensional scale for perceived social support (MSPSS). To determine the prevalence, descriptive analysis was used, followed by a t-test to compare gender differences and multiple regression analysis to examine associated factors. The sample comprised 56.4% of male respondents, and the mean age was 19.93. (SD: 1.28). Depression, anxiety, and stress were prevalent among 72.8%, 69.3%, and 57.3% of the participants, respectively. While sleep and appetite problems were strongly associated with depression, anxiety, and stress, previous mental disorder diagnoses and fear of poor grades only significantly correlated with depression and anxiety. Excessive internet use, on the other hand, was correlated with increased anxiety levels. Multiple regression analysis revealed that social support and dysfunctional attitudes explained 21% of the difference in students’ levels of depression, anxiety, and stress. Social support was the strongest predictor across all diagnoses. In conclusion, a high prevalence of depression, anxiety, and stress was reported among students, and the level of social support received was found to be the strongest predictor. Therefore, interventions aimed at expanding students’ social networks and access to social support are recommended.