Understanding university students’ daily activity patterns is essential for improving time management, academic performance, and overall well-being. This study investigates the time-use behaviors of Bangladeshi university students through an agent-based modeling approach. Data were collected via a survey of 224 students, covering 23 distinct activities tracked in 30-minute intervals over a 24-hour period. The model simulates activity transitions across weekdays and weekends, providing interactive, real-time visualizations using D3.js. Results reveal significant differences in activity patterns, with weekdays predominantly focused on academic tasks and weekends characterized by increased social and recreational engagements. Socioeconomic and demographic factors, such as gender and income level, also influence time allocation. This research demonstrates the effectiveness of agent-based modeling in capturing and visualizing complex behavioral patterns and offers insights for developing strategies to help students manage their time more effectively.