Accurate prediction of maize maturity is of great significance for efficient harvesting and agricultural machinery dispatch management. In order to predict the maturity of maize at the regional scale in advance, the 4day MODIS leaf area index (LAI) product was used as the data source, selecting the corn in Heilongjiang, Jilin and Liaoning Provinces as the research object, combined with agricultural meteorological data and global multimodel ensemble forecast data. The dynamic prediction of maize maturity in Northeast China was carried out ten days in advance by using the accumulated temperature-solar radiation model and the LAI curve integral area model. The research showed that the prediction results of the integral area model of LAI curve were optimal in terms of time efficiency and precision. The coefficient of determination (R2) of the LAI curve integral area model was 0.87, the root mean square error (RMSE) was 2.5d, and it was effectively better than that of the accumulated temperature-solar radiation model. The current maturity prediction method had limitations such as low spatial resolution and poor prediction timeliness. It showed that the LAI curve integral area model method had applicability in the prediction of largearea crop maturity.