A novel characterization method using artificial neural networks is presented. This method allows one to determine the intrinsic permeability tensor of ferrite thin-films from S-parameters measurements. Neural networks, efficient to solve inverse problems, are used to compute the permeability tensor components μ and k. This optimization technique is used to find extremely complex functions between inputs and outputs and can be successfully applied on our magnetic thin-film characterization problem. Results of our networks are compared to a theoretical model. A great number of both simulated and measured tests have been performed on many magnetic thin-films. Neural network processing leads to a rapid and robust method for predicting the magnetic characterization of thin-films in microwave range.