The construction industry is a complex, risk-prone, and dynamic sector. In India, rapid urbanization, strict deadlines, intensive labor activities, and changing safety rules strengthen these issues. A critical problem lies in balancing strict schedules and safety, as pressure to hurry frequently results in compromised actions, accidents, and delays. Traditional risk models consider safety and scheduling distinctly, failing to get the feedback-driven nature of delays, which comes from interrelated factors like fatigue, poor training, financial constraints, and weak hazard communication. On the other hand, the majority of studies take safety and scheduling separately, relying on assumptions and static models that disregard feedback loops and the project’s dynamic condition. Traditional scheduling excludes, moreover, few researches, especially in India connect early-stage safety measures to schedule reliability. Thus, this creates a clear gap for dynamic, data-driven models that represent and analyse safety–schedule interactions. This research addresses that gap by exploring this relationship in the Indian Construction Sector using a mixed-methods approach merging comparative case analysis, a 100-participant survey, SPSS-based statistical testing and analysis, and system dynamics (SD) simulation modelling in Python. Two projects, government-funded (Case A) and private-sector (Case B), were analyzed through accident, schedule, and safety investment records. Descriptive showed safety-related delays averaged 35.25% of overall delays, while the effect of schedule pressure on safety scored 3.81/5. Multiple regression portrayed safety climate positively predicted performance (β = 0.43, p = .001), whereas schedule pressure negatively (β = –0.35, p = .022). Correlation (r = 0.47, p < .002) demonstrated a moderate-to-strong positive relation between safety and schedule. Reliability tests indicated strong internal consistency for key factors such as Safety Climate (α = 0.88), Fatigue (α = 0.82), and Training Effectiveness (α = 0.86). System SD simulations portrayed that when safety measures were presented exactly after incidents, compliance enhanced, but increased fatigue and buffer use. Whereas, when safety measures were integrated from the beginning, accidents, fatigue, and delays were considerably reduced. A balanced strategy showed that early safety investment improves performance, positioning safety as a schedule enabler rather than a constraint. The findings offer a quantitative decision-support framework that allows managers, contractors, and policymakers to integrate safety into scheduling practices for optimal project outcomes.