Abstract This article introduces the concept of network entropy as a characteristic measure of network topology. We provide computational and analytical support for the hypothesis that network entropy is a quantitative measure of robustness. We formulate an evolutionary model based on entropy as a selective criterion and show that (a) it predicts the direction of changes in network structure over evolutionary time and (b) it accounts for the high degree of robustness and the heterogenous connectivity distribution, which is often observed in biological and technological networks. Our model is based on Darwinian principles of evolution and preferentially selects networks according to a global fitness criterion, rather than local preferences in classical models of network growth. We predict that the evolutionarily stable states of evolved networks will be characterized by extremal values of network entropy.