Hyperspectral images of egg samples were obtained using a hyperspectral system of 400~1 000 nm. The anomalous samples were detected by Monte Carlo method, and the original spectra were processed by three kinds of pretreatment methods. The characteristic wavelengths were extracted from the spectral data after pretreatment using competitive adaptive reweighed sampling (CARS), Genetic Algorithms PLS (GAPLS) and Interval Random Frog (IRF). The Partial Least Squares Regression (PLSR) and Least Squares Support Vector Machine (LS-SVM) eggs freshness prediction models based on full spectrum and characteristic wavelength were established respectively. The results showed that the standardized normal variate (SNV) method was the best pretreatment method. CARS, GAPLS and IRF were used to select 8, 35 and 74 characteristic wavelengths respectively. LS-SVM model based on characteristic wavelengths by GAPLS method was the best, and correlation coefficient of correlation (Rc) and prediction(Rp) of the model were 0.899 and 0.832 respectively. It was indicated that the non-destructive measurement for egg freshness based on hyperspectral imaging technology was feasible.