We propose a model of growing networks based on cliques formations. A clique is used to illustrate for example co-authorship in co-publication networks, co-occurence of words or collaboration between actors of the same movie. Our model is iterative and at each step, a clique of λη existing vertices and (1 − λ)η new vertices is created and added in the network; η is the mean number of vertices per clique and λ is the proportion of old vertices per clique. The old vertices are selected according to preferential attachment. We show that the degree distribution of the generated networks follows the Power Law of parameter 1 + 1/ λ and thus they are ultra small-world networks with high clustering coefficient and low density. Moreover, the networks generated by the proposed model match with some real co-publication networks such as CARI, EGC and HepTh.