Evaporation is the process by which water changes from a liquid to a gas or vapor. The evaporation rate is influenced by sun shine hours, temperature, relative humidity and wind speed. Historical data of this factor could be used to predict the evaporation rate by using different technique such as time series modeling, multiple regression analysis and artificial neural networks (ANN). In this paper, the ANNs are used to predict the evaporation rate in a semi-arid region knowing the basic climate factors. The collected data for Abyuha region, Egypt is used to train validate and test the network. Also, multiple linear and nonlinear regression methods are used to develop prediction models for predicting evaporation rates in terms of the same climatic factors. The results of the ANN model are compared to the best multiple linear regression (MLR) models. The analysis of the results indicated that the predictions of ANN are comparable to those of the regression methods and that ANN is a promising tool for modeling evaporation data. Sensitivity analysis indicated that the air temperature has a major effect on the evaporation rates while other factors have fewer effects.