This paper attempts to share some lessons learned by practitioners and researchers studying challenges of decision-making in the domain of major risks, either technological, natural or health diseases. Varying regulatory frameworks, different decision-making levels and scientific disciplines lead to a diversity of approaches which complicates the design of generic principles for decision-aiding for the prevention of low probability-high consequence events. In order to delineate the potential for improvement, several biases affecting prevention are addressed (in risk modelling and risk perception, especially of low probabilities). The proposed approach focuses on the analysis and quality assurance of the conditions of validity and legitimacy of decisions, implying several stakeholders and suggests the need for a better use of case studies.