The fundamental parameter method, empirical coefficient method, artificial neural network and some other methods are commonly used to establish the physical model between the count rate and the content of elements in the energy dispersive X-ray fluorescence analysis technique. Besides, through a large number of theoretical and experimental proof, as a new method of dealing with complex nonlinear problems, GMDH (group method of data handing) is better than most of statistical methods of calculation. And is a self-organizing learning in feed forward network, which could auto filter and determine its structure in the training process. Here, we are going to improve GMDH and give a quantitative prediction of the results. And both the reference values and forecast values of relative errors will be less than 5%, which make the method simple, reasonable, and reliable.