Political decisions (e.g. economic, fiscal, development) are often complex and multifaceted and involve many different stakeholders with different objectives and priorities. Very often decision-makers, when confronted with such problems, attempt to use intuitive or heuristic approaches to simplify the complexity until the problem seems more manageable. In this process, important information may be lost, opposing points of view may be discarded, and elements of uncertainty may be ignored. A crucial issue, when dealing with political decisions, is the radical uncertainty about the present (e.g. lack or poor quality of information) and also about the future. The latter one addresses the seeming paradox—how can we evaluate the rationality of our decisions today if the most important fact that we know about future conditions is that they are unknowable? In the literature it is mentioned that robustness analysis is a way of supporting government decision making when dealing with uncertainties and ignorance. However, so far no framework to deal with robustness in policy making, in a concrete and comprehensive manner, has been proposed. In the present research we discuss the different definitions and approaches of Robustness Analysis in government decision-making concerning the present and the future as a way to support the identification of potential robust strategies in policy circles. We also initiate the discussion on how facilitated forms of MCDA could tackle different aspects associated with government decision making and provide effective support in dealing with robustness of strategic decisions in designing complex policies with long-term consequences. We finally present some of our proposals introducing a holistic framework to deal with robustness issues in government decision-making.