Abstract: To enhance the precision and proactivity of safety management in university laboratories, this study utilizes complex network analysis on laboratory safety hazard data from Hebei Province (2020–2024) to construct a safety hazard co-occurrence network, revealing the interconnected structure and evolutionary patterns of hazards. The findings indicate that hazards related to chemical safety, experimental sites, and responsibility systems are closely linked and prone to triggering chain risks. The hazard structure shows a shift from being management-focused to facility- and operation-focused over time, with significant differences in hazard distribution across different types of universities. Based on these insights, a data-driven targeted intervention strategy is proposed across four dimensions—prevention, control, collaboration, and governance—providing theoretical support and a practical pathway for transforming laboratory safety management toward proactive prevention and systematic governance.