Ten years of NOAA GAC data over the Argentinean Pampa were analyzed in relation with climate and crop production. Correlations between crop yield and monthly NDVI (cumulated or not, weighted by the global radiation or not) reached 0.87 for wheat, 0.85 for soybean and 0.83 for corn, despite the classical limitations of AVHRR data (mixed response, atmospheric and directional noise, sensor calibration), the monthly frequency and the size of the test areas (10,000 km2). The quality of these results was partly due to the extensive character of the Pampa's cropping system since the correlation between final yield and NDVI relies on the following two hypothesis: NDVI can predict biomass and biomass is a good indicator of final grain yield. The best correlations were observed with the NDVI sensed at maximum green biomass, hence permitting yield estimations one to two months before harvest. Standard errors of regression were of 0.22, 0.17, and 0.63 t/ha for wheat, soybean, and maize respectively, for a mean yield around 1.7, 2.2, and 3.8 t/ha, respectively. Last, the complement between NDVI data and crop physiologically based models was examined. Despite the data related limitations, the relationship between CERES wheat predicted LAI and NOAA monthly GAC NDVI appeared as promising.