This paper presented a stochastic robustness analysis and synthesis procedure for the verification and clearance of flight control laws applied to major transport aircraft flight missions. The uncertainty parameters existed in the flight control system were modeled, and the Monte Carlo simulation was utilized to analysis the robustness of the flight control system in the heavy cargo airdrop operation. Moreover, stochastic robust synthesis method was adopted to enhance the robustness of the flight control system. The particle swarm optimization algorithm was adopted to search for a stochastic robust controller. Simulation results using a six-degrees-of-freedom nonlinear transport aircraft model demonstrated that the method reduced the sensitivity to uncertainty parameters and improved airdrop safety.