The decision-making process of pilot is a complex cognitive process that is critical to flight safety and efficiency. However, traditional approaches to studying pilot decision-making are often limited by cost, safety concerns, and data availability. This paper presents a rule-based simulation model designed to model and analyze human-centered pilot decision-making in flight. The model employs an Observation-Orientation-Decision-Action (OODA) loop framework constructed as a three-tiered decision-making hierarchy (Goal, Method, and Action), with decision rules derived from the pilot’s expertise. The digital pilot model based on this framework is integrated with a high-fidelity A320 flight simulator (Xplane12). To validate the human-centered nature of the platform, a comparison was made between simulation data and data collected from experienced A320 pilots performing the same flight tasks in the simulator. The comparison included flight parameters and physiological metrics. The results show that the performance of the digital pilot is relatively consistent with the behavior of the real pilot. This validates the platform’s ability to effectively model human-centered pilot decision-making. The platform offers a significant instrument for comprehending pilot cognition, investigating safety boundaries, and refining pilot training and cockpit automation systems.