It's very likely if we don't get any breakthroughs, [Malaysia Airlines flight MH370 is] at the bottom of the Indian Ocean and we will never find it, sadly Colleen Keller 
 
 "It still was a minor miracle that we found it," says Keller. Bayesian statisticians are particularly helpful in a search operation. New developments, such as information about how the plane’s communication systems were shut off, have lowered the probability that the plane disappeared because of an accident and increased the likelihood of deliberate diversion. Keller and her colleagues went through all the available information and assessed the uncertainties of each piece of data - applying Bayesian principles of probability to work out the most likely location of the plane. And if you find new information, you can revise your model easily. Targeting a search in an area requires a probability estimate for every point in that area, really a probability distribution. Among them: the hunt for the remnants of Air France Flight 447, which crashed in 2009 en route from Rio de Janeiro to Paris, killing all 228 people on board. “Search managers typically assume the search will be resolved quickly; only when it drags on do they realize they should have employed better record-keeping from the start,” Colleen M. Keller, a Metron senior analyst who worked with Stone on the Air France hunt, said by email. Debris from the Airbus A330 was found floating on the surface of the Atlantic five days later, but the mystery of why the plane crashed could only be answered by finding the black box and the cockpit voice recorder. First, the scientists calculated the probability the beacon would be heard within 1,730 meters as at least 90 percent. But how close together were the beacons — and if one beacon was damaged, was the other more likely to be? And that was just one piece of one adjustment to the scientists’ estimate of where they might find the plane wreckage. Then update to account for unsuccessful searches, and keep updating as new information comes in. It's either one or the other but it can't have gone both ways, but [Bayes] allows you to preserve all your theories and weight them."
– Forget satellite images and aerial searches—the best way to find Malaysia Airlines Flight MH370 may be with mathematical techniques dating back to the 18th century, the BBC reports. That's how Air France flight 447 was found in 2009, using "Bayesian statistics" to measure the probability of the plane being in one place or another. Named after Presbyterian minister and mathematician Thomas Bayes, the technique allowed experts to apply several factors to each point on a map: For example, what was the chance it crashed from mechanical failure? How far do planes tend to crash from their last known location? What was the chance that search teams missed debris in various locations? It's like picking a restaurant by balancing how full it is, what your favorite restaurant-review website says, and so on—except that experts hunting for Airbus A330 did that for each point where plane may have crashed in the Atlantic, Five Thirty-Eight notes. It was so hard that the US team of statisticians invited by France gave up, until they de-emphasized one statistic: that a plane's black box emits a signal after a crash 90% of the time. They changed their findings, and presto, the plane was found. Bayesian techniques have helped people find World War II U-boats, men overboard, and sunken treasure, but there's no evidence that Malaysia is employing them now. "I suspect that they just guess, like professional baseball managers used to do before Moneyball," says a biostatistician.