integration of satellite data with agroclimatic information can result in better procedures to evaluate the state and evolution of grain crops. in this work, phenologic calendar of corn (zea mays l.) crop based on growing-degree days procedures was integrated with normalized difference vegetation index (ndvi) estimations from global coverage of national oceanic and atmospheric administration-advanced very high resolution radiometer (noaa-avhrr) system. the main objectives were: i) to evaluate the relationship between ndvi and corn yield in different stages of crop cycle; ii) to analyze the influence of sowing date, and iii) to develop a predictive model of county (departmental) corn yield using satellite and ground data. the ndvi values accumulated in different corn phenologic stages showed a positive association with yield, and this relationship was modified in function of sowing date. the ndvi value during the reproductive stage, for any sowing date, always expressed a high association with corn yield, reaching significant correlation values (p < 0.05) in all cases, and even higher (p < 0.01) for some evaluated dates. the higher sensitivity showed by the reproductive stage confirms that it is a critical period. starting from this information, a prediction model was obtained that explains around 80% of corn yield variability of marcos juárez department in córdoba province, argentina.