Abstarct: The rapid growth of the world's population, the trend of increasing food production and the dispersion of global agricultural production reflects the fact that the supply of food for the people of the world is facing more frequent problems with the occurrence of the present, hence predicting the yield of agricultural products through remote sensing will play an important role in government macroeconomic decision making. In this regard, this research was aimed at finding a fast method with acceptable accuracy in order to predict the yield of winter wheat by using NDVI and LAI indices on the five farms located in Neyshabour, Khorasan Razavi province. The MODIS images of the TERRA satellite were conducted during the years 2012-2013 to 2014-2015. The results showed that there was a high correlation between NDVI and LAI indices (88 to 99%) over the years. The correlation between the observed performances with the LAI index varied between 2012-2013 and 2014-2015 so that in some years there was a strong correlation and in some years, a weak correlation. The correlation coefficient between 28% and 85% was applied in different agronomic years. The correlation coefficent between observed wheat yield and NDVI index was 92, 38 and 62 percent in 2012-2013, 2013-2014 and 2014-2015 respectively. The results of this experiment showed that vegetation indices changed in different fields and at different times during the growing season, so that the trend of changes in the indexes increased with approaching June and then decreased with approaching the wheat harvest time. baxsed on the results of this study, the sum of squared errors (RMSE) for the 10 calibrated farms was calculated to be 1.38 ton / ha, and the total squared errors (RMSE) was validated for 5 farms equal to 1.45 ton / ha. The magnitude of the RMSE indicates the possibility of accurate prediction of winter wheat yield by vegetation indices in Neishabour.