 A possible approach is suggested by an interpretation of Bayes’ law. If we combine Shannon’s notion of an optimal code with Bayes’ law, we get a rough theory about optimal model selection. Let \(\mathcal{H}\) be a set of hypotheses and let x be a data set. Using Bayes’ law, the optimal computational model under this distribution would be: 