Monitoring of crop conditions is important part for the agricultural development system of the country. The production and prediction of wheat yield have direct impact on national and international economies, and play an important role in the food management in Uzbekistan. Today wheat yield production in Uzbekistan is receiving considerable attention from governmental organizations and farmers. The objective of this study is to investigate how we can best predict wheat yield during the vegetation period in Tashkent province. The approach used in this study is based on a crop growth model which is able to quantify the effect of weather conditions on crop growth. The model focuses on indicators from Crop Growth Monitoring System (CGMS) and Remote Sensing data to use year to year variation of wheat yield in Tashkent province. The results showed the positive correlation between the predicted yield and field data (R2 = 0.87) and indicators maximum NDVI and maximum DMP which are driven from remote sensing data are performing the best at regional level
