Abstract: The problem of complex network reconstruction arises in situations where we want to study the properties of a complex network but do not fully know its structure. In such cases, it is necessary to seek methods that use only partial information to find a credible reconstruction of the given network, and then study the properties of interest on this reconstructed network. In this work, we introduce network models focusing on ensemble methods analogous tot those from statistical physics. Then, we propose to use the so-called Scale-Invariant Model, inspired by renormalization, for the reconstruction of complex networks.