Bayes’ theorem is used to quantify the impact of “new evidence” in three energy-related decision problems. The first problem concerns the risk of radioactivity release during the railroad transport of spent nuclear fuel. This history of shipments thus far is shown to make it highly unlikely that the frequency of release is on the order of 10−3 or greater per shipment. The second and third applications involve predicting the availability performance of new generations of turbine blades. Bayes’ theorem is demonstrated as a means for incorporating in the prediction the limited operational data on the new blades along with the experience of the earlier generation and the knowledge of the design changes.