Generally, various uncertain factors in practical engineering will affect the performance of flight vehicles. Thus, this chapter studies uncertainty-based multidisciplinary design optimization (Chen et al. in Theory and application of uncertainty-based multidisciplinary design optimization for flight vehicles. Science Press, 2013 [1]) (UMDO), which consists of analyzing system uncertainty and solving uncertainty-based optimization problems. This chapter begins with an overview of the basic concepts involved in UMDO, then briefs the sources and classifications of uncertainty and modeling methods. In addition, the uncertainty quantification methods are further introduced such as Monte Carlo method, Taylor expansion method, and deep arbitrary polynomial chaos expansion method. Finally, this Chapter introduces three multidisciplinary reliability-based optimization methods: the traditional two-layer nesting method, the single-layer sequential optimization method and the single-layer fusion optimization method.