Abstract
Two predictive, Bayesian distributions are introduced for deducing the size of future industrial accidents, natural disasters, and other incidences from limited information. The distributions derived from Pareto distributions incorporate both inherent variability and uncertainty. The procedure is illustrated by prediction of cumulative oil spill impacts. The extent to which risks could be estimated for planning purposes from limited data or scarce prior information by the Bayesian analysis is shown to be significant.