Background and Objectives: Computer Vision Syndrome (CVS) has become a major health problem among university students as a result of extensive electronic device use, but there is limited in-depth risk factor analysis by academic disciplines. The purpose of this study was to determine CVS prevalence, identify risk-associated factors, and investigate discipline-specific differences among university students. Methods: A cross-sectional study was conducted at Jazan University among 427 students of six academic disciplines between 2023 and 2024. Questionnaires validated by collecting demographics, electronic device usage patterns, eye care practices, and CVS symptoms were used to assess the data. Statistical analyses involved chi-square tests and multivariable logistic regression with significance at p < 0.05. Results: Prevalence of CVS was at epidemic proportions at 89.7% (95% CI: 86.8–92.6%), which was much higher than global averages. Considerable inter-disciplinary heterogeneity occurred, from 95.3% in Computer Science to 75.4% in Arts and Humanities students. A strong dose–response gradient was found for duration of device use: 3–4 h (OR = 4.13, 95% CI: 1.13–5.57), 5–6 h (OR = 5.31, 95% CI: 1.46–9.86), and ≥7 h per day (OR = 6.25, 95% CI: 1.74–8.01) versus 1–2 h use. Students >24 years old demonstrated a very high risk (OR = 9.73, 95% CI: 1.53–19.65). Headaches were the most common symptom (68.0%), and adoption of protective measures was low. Conclusions: This work demonstrates epidemic-level prevalence of CVS with unequivocal dose–response relationships and discipline-specific risk patterns, offering evidence-based targets for immediate campus-wide interventions and identifying a vital post-pandemic public health challenge meriting immediate attention.