In this paper, we explore the objective-Bayesian principle of minimum information and Maximum Entropy as a solution to the problem of awareness growth: how should rational agents adjust their beliefs upon becoming aware of new possibilities? We introduce the Maximum Entropy principle as a theoretical solution to the problem of awareness growth and present the results of two experiments conducted to compare human reasoners’ responses with the theoretical prescriptions of the Maximum Entropy approach. We discover that, although the MaxEnt method may appear computationally demanding, participants’ responses are largely consistent with the theoretical prescription.