In this paper an adaptive neuro-fuzzy inference system (ANFIS) model has been developed for the prediction of thermophysical properties of R417A. Temperature and pressure values were taken as model's input features. Thermophysical properties as heat conduction coefficient, dynamic viscosity, kinematic viscosity, thermal diffusivity, density, specific heat capacity were determined by means of ANFIS. The statistical methods, such as the root-mean squared (RMS), the coefficient of multiple determinations (R-2) and the coefficient of variation (cov), are given to compare the predicted and actual values for model validation. The thermophysical property results estimated by using the developed model are strongly in agreement with the actual results. Results obtained show that ANFIS can be used as an alternative way for determining of thermophysical properties of new refrigerant. Therefore, instead of limited data found in the literature, thermophysical properties for every temperature and pressure value are obtained using hybridized structures such as ANFIS. This method will help to thermodynamic simulation of refrigeration system.