Among a heap of books claiming that science proves God’s existence emerges one that computes a probability of 67 percent. The physicist author of The Probability of God, Stephen D. Unwin, begins with a 50 percent probability that God exists (because 50–50 represents “maximum ignorance”), then applies a modified Bayesian theorem. Plugging his figures for six lines of evidence into the formula in sequence, Unwin concludes: “The probability that God exists is 67%.” He then notes that this number has a subjective element since it reflects his assessment of the evidence.

This Yale faculty page states that Bayes’ theorem has been discussed in connection with arguments about Christianity and religious belief. It also notes that Bayes’ theorem can be used in reasoning about claims such as the probability that an event occurred given evidence, which is the basic structure behind Bayesian arguments about God’s existence.

The abstract describes the work as an examination of “Richard Swinburne's probabilistic Bayesian argument for the existence of God” and a critical analysis of his use of prior probability. It notes that Swinburne uses Bayes’s theorem to argue that “even if the initial prior probability of the hypothesis of theism is taken to be equiprobable with competing hypotheses, its likelihood on the evidence is higher, resulting in a favourable probability outcome once all a posteriori evidence has been assessed.” This characterizes Swinburne’s project as a formally Bayesian estimation of how probable theism (and thus God’s existence) is, given various kinds of evidence.

According to Hume, the probability of people inaccurately claiming that they'd seen Jesus' resurrection far outweighed the probability that the event actually occurred. The page discusses Bayes’ theorem in the context of arguments about religious claims, including Christian claims about miracles and resurrection.

This thesis explicitly refers to the likelihood of God’s existence as a prior that can be used in Bayesian reasoning. It says that if the probability of God’s existence is believed to be higher, then the probability of the Resurrection hypothesis increases, and it discusses computing posterior probabilities using Bayesian methods.

The publisher’s description states that Swinburne “uses the principles of inductive and Bayesian reasoning to argue that, on balance, it is more probable than not that God exists.” It explains that he weighs a wide range of evidence—such as the existence of the universe, order in nature, consciousness, moral awareness, and religious experience—within a Bayesian framework to estimate the overall probability of theism. The book is presented as a systematic, probabilistic case that the hypothesis that God exists has a favorable probability when all the evidence is taken into account.

While focused on the historical question of Jesus’ existence, the post outlines the general Bayesian approach used by some religious and skeptical writers. Ehrman explains that Bayes’ theorem starts with prior probabilities for hypotheses and then updates them with likelihoods of observed evidence, resulting in a posterior probability for each hypothesis. He notes that some people have tried to use this framework to get “a definite probability” for historical or religious claims, though he is skeptical that precise numerical values can be justified for such complex events. This provides context for how Bayesian calculations are applied in debates involving religious and theological claims.

So how do you set about calculating the probability that God exists? Unwin says that we should use something called Bayesian probability theory to do so. His exposition of how this works is within reach of even the most mathematically averse reader and he constructs an equation that allows him to handle lots of different kinds of evidence. Unwin suggests six categories: morality, providence, miracles, natural evil, moral evil and religious experience. Using his chosen parameters, he ends up with a probability for the existence of God that is greater than 50 percent.

Stephen Unwin published a book-length Bayesian argument in 2003 that assigns a numerical probability to God’s existence and concludes with an estimate of 67%. This is a secondary book, not a peer-reviewed journal article, but it is the best-known published Bayesian analysis making that claim.

Unwin, a physicist and risk management consultant and author of The Probability of God, set as his objective “to calculate the numerical probability that God exists.” The simple answer is Bayes Theorem. He distinguishes a Bayesian approach to probability from a frequentist one and then takes the evidence one has, converting the ‘data’ into a mathematical formula and thus a probability. Unwin starts with the proposition that he is neutral on God’s existence – a starting point of 50/50 – and then uses six evidentiary areas (goodness, moral evil, natural evil, intra-natural miracles, extra-natural miracles, religious experiences), each assigned a numeric factor, to update this prior. The reviewer notes that Unwin ends up with a number “north of 50%.”

This article discusses Stephen Unwin’s Bayesian calculation and reports that Unwin concludes: “The probability that God exists is 67%.” It also explains that the number is based on subjective assessments of evidence.