Introduction: Computer Vision Syndrome (CVS) is a common occupational health problem among individuals who use digital devices for prolonged periods, particularly university students. Computer Vision Syndrome encompasses a range of ocular and extra-ocular symptoms that may negatively affect academic performance and quality of life. Objective: To determine the magnitude of Computer Vision Syndrome and identify associated factors among medical students at Bahir Dar Universityfrom October 2025 to December 2025. Methods: An institution-based cross-sectional study was conducted at Bahir Dar University among 356 medical students from October 2025 to December 2025. Data were collected using a structured, self-administered questionnaire for assessing socio-demographic characteristics, digital device use, health and behavioral factors, and CVS-related symptoms, with participants selected through stratified random sampling.Descriptive statistics were used to summarize the data. Bivariate and multivariable logistic regression analyses were performed using SPSS version 27.0 to identify factors associated with CVS. Statistical significance was declared at P < 0.05. Results:Among 356 medical students, 274 students (77%; 95% CI: 72.3–81.0) reported experiencing at least one symptom of Computer vision syndrome. The most commonly reported symptoms were eye strain or pain (28.4%), itching sensation (26.7%), burning sensation and eye redness (25.3% each), and headache (24.7%). Nearly half of the participants (49.4%) experienced a mild symptom burden, while 27.0% and 11.2% reported moderate and high symptom burdens, respectively. In multivariable logistic regression, independent predictors of the outcome included smartphone use (AOR = 2.48, 95% CI: 1.30–4.75, P= 0.033), computer use >8 hours/day (AOR = 2.39, 95% CI: 1.18–2.95, P= 0.018), daily caffeinated beverage consumption (AOR = 2.24, 95% CI: 1.05–4.77, P = 0.036), and poor self-rated eye health (AOR = 3.20, 95% CI: 1.50–6.80, P< 0.001) were significantly associated with CVS. Conclusion and recommendation: Computer Vision Syndrome was highly prevalent among university students. Prolonged screen exposure, smartphone use, poor perceived eye health, and caffeinated beverage consumption were significant predictors. Preventive strategies, including awareness creation, behavioral modification, and promotion of healthy screen-use practices, are strongly recommended. Keywords: Computer Vision Syndrome, Digital Device Use, University Students, Eye Health, Ethiopia