A system and method for detecting, predicting, and managing irreversible state transitions in complex systems using collapse-based modeling. The system computes a collapse metric derived from current system states, historical trajectories, interaction effects, and dynamic acceleration behavior. A multi-dimensional collapse surface is generated through parameter simulation to identify stable and unstable regions. A decision engine produces control actions, including continuation, adjustment, or termination, with asymmetric weighting to prioritize avoidance of irreversible negative outcomes. The system enables real-time monitoring and intervention across domains including drug discovery, biological systems, financial risk management, and engineered systems, providing a deterministic framework for managing threshold-driven transitions.