This project applied an Agri-meteorological model (FAD AquaCrop v4) to predict the likely changes in the yield of rain-fed grain crops in Iraqi Kurdistan resulting from projected climate change. The research was carried out in three main stages. Firstly, Landsat Thematic Mapper imagery was used to classify the study area into different land cover types. The effect of rainfall variability on vegetation productivity in areas classified as 'rain-fed agriculture' was determined using a monthly composite time series of Normalised Difference Vegetation Index (NDVI) measurements from July 1981 to December 2006 derived from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR). These data were compared to monthly precipitation records from Sulaymaniyah Meteorological Station to characterise the nature of vegetation response to rainfall. A strong positive correlation was found between vegetation productivity and precipitation patterns with a 2-month lag period. The second stage involves applying the AquaCrop model to predict winter wheat crop performance for the growing seasons 1986-2006. It was found that the simulated grain yield (GY) and above ground biomass (AGB) were consistent with the measured GY and AGB, with corresponding coefficients of determination (r) of 0.85 GY and 0.81 AGB. These results indicate that the AquaCrop model can be used for predicting winter wheat grain production. The last stage involved studying the impact of projected climate change for the 2020, 2050 and 2080 derived from the HadCM3 General Circulation Model. The AquaCrop model was re-run using the predicted changes in the climate values for temperature/precipitation for the selected decades, to simulate the impact on winter wheat yields. The findings indicate that the average yield of rain-fed crops will be reduced, with scenario A2a experiencing more reduction relative to that predicted by scenario B2a.