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The Golden Delicious apple shelf-life prediction model based on electronic nose was built by partial least squares regressions (PLSR). Sensory quality, such as, weight loss, texture, color changes and electronic nose were studied. The correlation between the electronic nose sensors and the sensory quality of Golden Delicious apples were analyzed to select the appropriate sensors for the construction of the shelf-life model. The results of the shelf-life prediction model on Golden Delicious apples building by PLSR showed that R2 of training set was 0.86, RMSEC was 3.94. The R2 of prediction set reached to 0.98, and the model was relatively accurate.