Uncertainty is always present whenever it comes time to make a decision, due to either incomplete knowledge or intrinsic variability of the decision process. Within the GDSI context, risk analysis and life cycle assessment are the two pillars of decision making. It is therefore essential to address uncertainties in decision analysis integrating both risk and sustainability aspects. Probability is the primary instrument to represent and quantify uncertainty arisen from a variety of sources, while statistics is used to analyse and interpret available data. Apart from the generic handling of uncertainties, it is crucial to deal with methodological and computational challenges in different decision-making cases. Stochastic and statistical models are applied to several domains, such as urban water management, transport infrastructure modeling and food production and consumption. The common principles and methods for decision making under uncertainty, across various scientific fields, lead to the development of an interdisciplinary toolbox, including a selection of mathematical tools, metrics and associated data. The forenamed toolbox is directly related to the generic framework for sustainability- and risk-informed decision support established by GDSI.