 A more interesting answer to the above question of how explanation is to guide one’s choice of priors has been given by Jonathan Weisberg (2009). We said that mainstream Bayesians regard one assignment of prior probabilities as being as good as any other. So-called objective Bayesians do not do so, however. These Bayesians think priors must obey principles beyond the probability axioms in order to be admissible. Objective Bayesians are divided among themselves over exactly which further principles are to be obeyed, but at least for a while they agreed that the Principle of Indifference is among them. Roughly stated, this principle counsels that, absent a reason to the contrary, we give equal priors to competing hypotheses. As is well known, however, in its original form the Principle of Indifference may lead to inconsistent assignments of probabilities and so can hardly be advertised as a principle of rationality. The problem is that there are typically various ways to partition logical space that appear plausible given the problem at hand, and that not all of them lead to the same prior probability assignment, even assuming the Principle of Indifference. Weisberg’s proposal amounts to the claim that explanatory considerations may favor some of those partitions over others. Perhaps we will not always end up with a unique partition to which the Principle of Indifference is to be applied, but it would already be progress if we ended up with only a handful of partitions. For we could then still arrive in a motivated way at our prior probabilities, by proceeding in two steps, namely, by first applying the Principle of Indifference to the partitions separately, thereby possibly obtaining different assignments of priors, and by then taking a weighted average of the thus obtained priors, where the weights, too, are to depend on explanatory considerations. The result would again be a probability function—the uniquely correct prior probability function, according to Weisberg.