<![CDATA[Decision-making under uncertainty is a major challenge in management, economics, and public policy, where outcomes cannot be accurately predicted due to limited information and environmental dynamics. This article conducts a systematic literature review of risk and probability approaches to decision-making under uncertainty, focusing on rational theory synthesis (such as expected utility theory, decision tree analysis, and Bayesian decision theory) and behavioral perspectives (prospect theory and heuristics). The review covers reputable literature from the last ten years to the present. The results show that the probabilistic approach provides a strong and adaptive rational framework, but has significant limitations due to cognitive biases such as loss aversion, overconfidence, and ambiguity aversion, which cause deviations from normative rationality. The integration of rational approaches with behavioral elements, through hybrid models, has proven to be more comprehensive and realistic for dealing with true uncertainty (Knightian uncertainty). These findings emphasize the need for a multidimensional decision-making paradigm in organizational and policy practices.]]>
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