This text mainly aims at the dry manufacturing process of an agriculture No.12 peanut. In order to monitoring the water content of the peanut during the drying process, the polynomial network is used to construct a water content prediction model. The polynomial network is constituted with several function nodes; these function nodes can be self-organizing into the optimal network structures according to the predicted square error (PSE) criteria. It is shown that the polynomial network can correctly correlate the input variables (drying temperature, initial water content and drying time) with the output variable (water content). Based on the water content prediction model constructed, the water content of the peanuts can be predicted with reasonable accuracy if the drying conditions are given and it is also consistent with the experimental results very well.