Light use efficiency is an important parameter of plant productivity model. It is an evaluation index for plant to turn the solar energy into dry matter efficiency. Taking cucumbers as the study objects, a method for light use efficiency prediction was proposed with the help of analysis technique of laser-induced chlorophyll fluorescence spectra based on the theory of support vector machine (SVM). Chlorophyll fluorescence spectra, net photosynthetic rate and photosynthetic active radiation of cucumber leaves were synchronously acquired, and the 500~800nm band of chlorophyll fluorescence spectrum was selected as study objects. Firstly, the original spectra was pretreated by SG—FDT method. Secondly, the characteristic values of pretreated spectra were extracted by using principal component analysis (PCA) method, the first ten principal components whose cumulative contribution rate was 93.49% were selected instead of the original spectral information in the study. Finally, the prediction model of light use efficiency was established through the SVM with the radial basis function. The penalty parameter C and kernel function parameter g were ultimately determined as C=0.03125, g=1 by carrying out a large number of tests, and then 60 training samples were combined to train the model. Ten testing samples were used to test the established model, and the results showed that the average error of the testing samples was 8.94%, which indicated a good predictive power.