Due to the complex buckling behavior, failure mechanisms, and various uncertain factors associated with composite stiffener panels, there are limited reports on failure reliability analysis that take these uncertainties into account. To address this issue, this study focuses on a typical composite reinforced panel from a specific aircraft. By considering uncertainty factors such as material properties, geometric parameters, and loading conditions, a BP neural network proxy model was developed. Reliability analysis was then conducted using Monte Carlo simulation, providing valuable insights for the reliability design of large composite structures in civil aircraft.