A statistical flight plan optimization framework is developed, and a simplified version solved for a hypothetical distress situation. The framework proposed herein attempts to increase overall survivability by evaluating and optimizing the probable outcome of various flight plans, given a statistical representation of the probable outcomes of each flight plan and their respective probabilities of success. This work attempts to solve the problem using a simplified probability model and safety metric. An airport grouping strategy that groups the airports prior to path derivation is also developed to identify the convex sub problems of the non convex, continuous-discrete overall problem. The performance of this newly developed probabilistic trajectory algorithm is evaluated using numerical simulations which include variable failure rates to simulate different in-flight distress conditions, and multiple turns to accommodate realistic trajectories. The results show that it is possible to increase aircraft survivability by using this algorithm.