Predicting crop mature date and producing harvesting order is an important field of applying remote sensing in precision farming. Current crop phenophase monitoring method with remote sensing cannot meet the needs of precision farming, due to its low spatial resolution and time lag in information acquiring. Taking Yucheng (Shandong) as study area, this paper analyzed the dynamic variation of moisture content and chlorophyll in the maturing period of winter wheat to provide theoretical basis for mature date prediction. Winter wheat mature date predicting model was developed through regression analysis by using VI from HJ-1A CCD to describe the change of chlorophyll and NDWI from HJ-1B IRS to describe the change of water content. The winter wheat mature date map of Yucheng was produced. The a correlation between predicted and observed mature dates has reached very significant level. A rather consistent maturing order could be concluded. Taking the predictions with errors less than 1 day as successful prediction, the accuracy was 65%. The study showed that HJ-1A/1B data can be effectively used for winter wheat mature data prediction, universal predicting model with remote sensing data of different temporal period will be the focus in the following research.