Splash rain erosion, as the first event in soil erosion, causes the movement of soil particles and lumps, and it is considered as an important process in erosion. Given the complexity of this process in nature, one way of identifying and modeling the process is to use a rain simulator and to study it in the laboratory. For this purpose, in the present study the simulation of the amount of material transported in the various intensities of rainfall and for different amounts of poly-acryl-amide was done. After measuring the amount of material transported in different durations and amounts of poly-acryl-amide, using artificial neural networks, ANFIS and SVM, the modeling of transported materials was done. The results showed that among the three methods used, the best values of evaluation criteria are related to SVM and ANFIS respectively. Among the three studied durations, also the best results are related to the experiment with duration of 30 minutes. The results showed that, based on available data, by increasing the number of membership functions, extra-fitting happens in the ANFIS method. To reduce the complexity of the model and the likelihood of extra-fitting, some of the rules was eliminated. The results showed that the performance of the model was improved by eliminating some rules.