Cationic degree has been investigated as an important factor in polyacrylamide materials. Diallyl dimethyl ammonium chloride and acrylamide (PDA) was grafted by free radical polymerisation of acrylamide monomer (AM) onto the cationic monomer dimethyl diallyl ammonium chloride (DMDAAC). In the present study, near infrared reflectance spectroscopy(NIRS) was used as a rapid and accurate method to determine the cationic degree in the PDA. In this experiment, the near infrared spectra of 37 PDA samples that were self-prepared in the laboratory from 900.00 to 1 700.00 were collected. The characteristic peaks and the entire spectrum segment as the input layer neurons in radical basis function(RBF) were investigated for establishing the mathematical conversion NIRS calibration mode. For reduction of the NIR spectrum noise, the wavelet analysis was used as pretreatment process. The measured value was determined by using precipitation titration and a comparison between the simulated value and measured value was made. It was found that the external validation determination coefficient was more than 0.9, and the simulation value is in good agreement with the measured value. The statistics analysis showed that there was no significant difference between simulated value and measured value. Therefore, the calibration model (RBF neural network) established in this paper exhibited a remarkable feasibility for predicting the cationic degree of PDA based on the near infrared spectroscopy.