In order to explore the feasibility of predicting vitamin C content of Lingwu long jujube based on dielectric spectrum and find the best predictive model. Dielectric spectrum of Changzao were tested and analysed under of 1kHz~1MHz using the LCR tester. The characteristic frequency points were screened out by Competitive Adaptive Reweighed Sampling， Genetic Algorithm， Successive Projection Aalgorithm， and Uninformative Variable Elimination and the predictive model of Vitamin C content Least square support vector machine and Partial Least Squares were established combining the characteristic frequencies and VC value. The results show that the UVE algorithm is the best method to screen spectrum and 38 characteristic frequency points were screened. UVE-PLS is the best predictive model， the Rc， RMSEC， Rp， RMSEP values were 0.9871， 3.9322， 0.9460， 4.0400 and no significant difference （P>0.05） between measured and predicted values of validation model. It is feasible to predict the content of VC in long jujube based on dielectric spectrum.