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In this paper a new method for linear modeling of nonlinear systems is presented. The method is based on the design of an artificial neural network with two layers. The network is trained only according to the input- output data of the system. The weights of connections in this network, represents the coefficients of the transfer function. For systems with linear behavior the method of least square error (LSE) represents the best linear model of the system. However, for nonlinear systems, such as some subsystems in power plants boilers LSE does not represent the best linear approximation of the system. necessarily. In this paper a new linear modeling method is presented and applied to some subsystems in a power plant boiler. Comparison between the transfer function obtained in this way and by LSE method, shows that the neural network method gives better linear models for these nonlinear systems.