Uncertainty is an inherent part of portfolio construction. Capital markets are simply too complex to capture every nuance and detail in our models. As investors, we are tasked with finding techniques to characterize and mitigate the uncertainties we face. The robust optimization approach provides an opportunity to explicitly model uncertainty and build portfolios that protect against its ill effects. In this paper, PGIM Quantitative Solutions' Global Multi-Asset Solutions (GMS) team shows how to build robust portfolios that model investment uncertainty and protect against its ill effects. The team presents a number of simple models that are intuitive, easy to define, and computationally attractive.