 There is a deeper problem with the probabilistic conception of the standard of proof. There does not seem to be a satisfactory interpretation of probability that suits the forensic context. The only plausible candidate is the subjective meaning of probability according to which probability is construed as the strength of belief. The evidence is sufficient to satisfy the legal standard of proof on a disputed question of fact—for example, it is sufficient to justify the positive finding of fact that the accused killed the victim—only if the fact-finder, having considered the evidence, forms a sufficiently strong belief that the accused killed the victim. Guidance on how to process evidence and form beliefs can be found in a mathematical theorem known as Bayes’ theorem; it is the method by which an ideal rational fact-finder would revise or update his beliefs in the light of new  evidence.[19]  To return to our earlier hypothetical scenario, suppose the fact-finder initially believes the odds of the accused being guilty is 1:1 (“prior odds”) or, putting this differently, that there is a 0.5 probability of guilt. The fact-finder then receives evidence that blood of type A was found at the scene of the crime and that the accused has type A blood. Fifty percent of the population has this blood type. On the Bayesian approach, the posterior odds are calculated by multiplying the prior odds (1:1) by the likelihood ratio (which, as we saw in  section 2.1.2  above, is 2:1). The fact-finder’s belief in the odds of guilt should now be revised to 2:1; the probability of guilt is now increased to 0.67 (Lempert 1977).