Jujube as one important economic crop in Southern Xinjiang was used to analyze the relationship between raw spectra and first-order differential spectra of jujube leaves and the content of total nitrogen with hyperspectral techniques. A model for predicting the content of nitrogen was established to provide a theoretical basis for nitrogen monitoring and precise fertilization during jujube cultivation. Spectral sensitive variables were used to construct vegetation indices as derivative variables. Multiple linear and nonlinear models for predicting the content of nitrogen were established using derivative variables as variables. The accuracy of models for predicting the content of nitrogen was tested. Results showed that the fitted decision coefficients of models based on the original spectra and first-order differential spectra of jujube trees were greater than 0.75. The overall prediction performance of the original spectral variables was better than that of first-order differential spectra. The best prediction was based on the power function model of the original spectral variables 4： Nit =1.097x^0.735， R²=0.821， and RMSE=0.024 5. It is indicated that the model established for predicting the content of nitrogen can achieve good effect of monitoring nitrogen in jujube tree based on hyperspectral reflectance characteristics， and can serve as an important theoretical basis for the nutrient diagnosis of jujube tree.