Troubleshooting and decision support system with reasoning is an active research topic, and causal analysis for complex component interactions in complex systems has remained a critical challenge to be overcome. We developed an innovative, constraint-based causal analysis to better detect, isolate, and troubleshoot complex systems. The feasibility of the causal Bayesian network (CBN) approach has been proven with implementation using test data acquired from electromechanical actuator (EMA) systems. The validation step is facilitated by comparing the trained CBN with original structure and shows the flexibility and extensibility of our solutions. This causal analysis processing in integrated system health management (ISHM) will enable enhancements in flight safety and condition-based maintenance (CBM) by increasing availability and mission-effectiveness while reducing maintenance costs.