A key issue in complex systems design is measuring the ‘goodness’ of a design, i.e. finding a criterion through which a particular design is determined to be the ‘best’. Traditional choices in aerospace systems design, such as performance, cost, revenue, reliability, and safety, individually fail to fully capture the life cycle characteristics of the system. Furthermore, current multi-criteria optimization approaches, addressing this problem, rely on deterministic, thus, complete and known information about the system and the environment it is exposed to. In many cases, this information is not be available at the conceptual or preliminary design phases. Hence, critical decisions made in these phases have to draw from only incomplete or uncertain knowledge. One modeling option is to treat this incomplete information probabilistically, accounting for the fact that certain values may be prominent, while the actual value during operation is unknown. Hence, to account for a multi-criteria as well as a probabilistic approach to systems design, a joint-probabilistic formulation is needed to accurately estimate the probability of satisfying the criteria concurrently. When criteria represent objective/ aspiration functions with corresponding goals, this ‘joint probability’ can also be called viability. The proposed approach to probabilistic, multi-criteria aircraft design, called the Joint Probabilistic Decision Making (JPDM) technique, will facilitate precisely this estimate.