Nowadays, the water use efficiency is very important in agricultural management. One of the ways that have been taken into consideration to improve the water use efficiency in agriculture is the use of greenhouses. The greenhouses are important because we can manage the planting and use water with great precision in the greenhouse. Evapotrairation is the most important parameter in the management of irrigation and greenhouse crops in particular. The evapotrairation of each crop varies depending on growth stage and meteorological conditions inside greenhouse. Changes in evapotrairation during the crop growth cycle, defines the ratio between crop evapotrairation and reference evapotrairation that named crop coefficient (Kc). Knowing crop evapotrairation at any time is very important in the management of irrigation systems for greenhouse. This study was conducted to determine cucumber, tomato, peppers evapotrairation at Isfahan University of Technology greenhouse using micro-lysimeter, from 4 January 4, 2009 to August 6, 2009. To determine the water balance of soil micro-lysimeters the gravimetric method was used. Simultaneously, reference evapotrairation estimated using drainage lysimeters and a reduced evaporation pan. The results indicate the total reference evapotrairation in 7 months of the study was 824 mm. The total evapotrairation for cucumber in 3.5 months growth cycle obtained as 202 mm. For tomato in 6 months and pepper in 7 months growth cycle, evapotrairation obtained as 524 and 667 mm, respectively. Weekly changes in crop coefficients of different cultures in the growth cycle indicated a variable process. Crop coefficient increased at the initial growth cycle, fixed at the matured stage and decreased at the late stage of growth. For cucumber values of coefficients at the initial, development, midseason and late season obtained as 0.41, 0.69, 0.98 and 0.77 respectively. For the tomato, values obtained as 0.44, 0.68, 1.15 and 0.68 and for pepper obtained as 0.25, 0.53, 1.03 and 0.75, respectively. To find the relationship between meteorological data and crop height with crop evapotrairation, crop water use modeled using . The results indicate that the best model proposed is a nonlinear regression based on the average daily temperature of air, solar radiation and crop height. To assess the accuracy of artificial neural networks in estimation of crop evapotrairation, minimum and maximum air temperature, relative humidity, solar radiation and crop height selected as model input. Process modeling has shown that similar to the non-linear regression, the Keywords: Greenhouse, Evapotrairation, Crop coefficient, Cucumber, Tomato, Pepper, Artificial Neural Networks.