In recent years there have been a number of highly publicized searches for missing aircraft such as the ones for Air France flight AF 447 and Malaysia Airlines flight MH 370.

Bayesian search theory provides a well-developed method for planning searches for missing aircraft, ships lost at sea, or people missing on land. The theory has been applied successfully to searches for the missing US nuclear submarine Scorpion, the SS Central America (ship of gold), and the wreck of AF 447. It is used routinely the by U. S. Coast Guard to find people and ships missing at sea.

This talk presents the basic elements of the theory. It describes how Bayesian search theory was used to locate the wreck of AF 447 after two-years of unsuccessful search and discusses how it was applied to the search for MH 370. A crucial feature of Bayesian search theory is that it provides a principled method of combining all available information about the location of a search object. This is particularly important in one-of-a-kind searches such as the one for AF 447 where there is little or no statistical data to rely upon.