The need to design systems under uncertainty arises frequently in applications such as telecommunication network configuration, airline hub-and-spoke/inter-hub network design, power grid design, transportation system design, call center staffing, and distribution center design. Such problems are very challenging because: (1) design problems with sophisticated configuration requirements for medium to large scale systems often yield large-sized linear/nonlinear mathematical models with both continuous and discrete decision variables, and (2) in most cases input parameters such as demand arrival rates are subject to uncertainty, whereas engineers have to make a design decision "today,'' before the outcomes of the uncertain parameters can be observed. The purpose of this study was to develop proactive modeling methodologies and effective solution techniques for such system design problems. Particular emphasis was placed on a network design problem with connectivity and diameter requirements under probabilistic edge failures and a service system capacity planning problem under uncertain demand rates.