Landing is a crucial phase during an aircraft's operation, which is divided into manual and automatic landing. Aircraft equipped with automatic landing capabilities can adapt to a wider range of operational scenarios, significantly enhancing their market competitiveness of the aircraft. Through research, it has been found that airworthiness standards related to automatic landing performance are mostly probabilistic indicators. To verify whether an automatic landing system meets the performance requirements of the airworthiness criteria's probabilistic indicators, extensive Monte Carlo simulations need to be conducted, and the probability model of interference factors needs to be set to be consistent with the actual flight scenario probability model. Capturing the requirements for automatic landing based on relevant airworthiness criteria, and using quality function deployment （QFD） tools, these requirements were transformed into three key functional elements for automatic landing simulation: probability distribution fitting, simulation iteration determination, and Monte Carlo calculation method. These three functional elements were organized and categorized using tools like QFD affinity diagrams. Further methods such as cross-validation and orthogonal experiments were employed to determine the final solution. The chosen solution was then applied in the simulation of an automatic landing system to confirm the feasibility of the Monte Carlo simulation method for automatic landings.