Developed by the U.S. Navy in response to the German submarine threat in the Atlantic Ocean during World War II, Bayesian search theory is a systematic mathematical method for planning searches for lost objects. It has been used to plan successful searches for lost submarines (USS Scorpion [5]), aircraft (Air France Flight 447 [7]), and treasure ships (SS Central America [6]). Bayesian search theory is the analytic core of the U.S Coast Guard’s national Search and Rescue Optimal Planning System (SAROPS), credited with helping save scores of lives, including that of John Aldridge.