Network models have received increasing attention from the statistical community, in particular in the context of analyzing and describing the interactions of complex random systems. In this context, community structures can be observed in many networks, where the nodes are clustered into communities with the same connection patterns. In this talk, we will discuss the problem of estimating the number of communities for the Stochastic Block Model (SBM) and the Degree Corrected Stochastic Block Model (DCSBM). In general, we will discuss penalized methods used to infer the number of communities given a network.