The aim of this research is to study two intelligent systems including artificial neural network and multi – layer adaptive neuro-fuzzy inference system (ANFIS) for modeling the output energy in production of greenhouse and open-field cucumber. In order to determine the pattern of consumed energy, the required information was collected directly from the 160 cucumber beneficiary. By analyzing the results, the average input and output energy was respectively equal to 1159901.1 MJ and 173985.256 MJ for greenhouse cucumber production and respectively 75648.11 MJ and 22694.433 MJ for open-field cucumber production . The maximum input energy in production of greenhouse and open-field cucumber was related to fuel and electricity respectively. The minimum input energy was related to seed energy. Using the input and output energy data, modeling of output energy was performed based the input energy and using the mentioned modeling methods. Refer to the results of ANFIS model, the values of coefficient of determination and root mean square error for greenhouse and open-field cucumber were equal to 0.9924, 9920 and 0.051 and 0.0130, respectively, Furthermore, these values were determined using the neural network modelwith optimum structure of (8-10-1) for greenhouse cucumber and structure of (8-12-1) for open-field cucumber. It was revealed that the coefficient of determination value was equal to 0.9492 and 0.9785, and RMSE was equal to 0.0121 and 0.0418, respectively. The result.