Knowledge representation is key factor for problem representation particularly for incomplete information in expert systems. Usually incomplete information is fuzzy rather than likelihood. Learning methods are necessary to solve expert problems. The conditional inference method is studied different from Zadeh, Mamdani and TSK methods. Learning fuzzy conditional inference with individual methods fuzzy logic, Genetic algorithms, Petri net and neural net not sufficient for large problems. In this paper FuGePeNuNet method is studded by combining fuzzy logic, Genetic algorithms, Petri net and Neural net for large problems of Fuzzy Expert Systems. The fuzzy medical diagnose is given an example.