Multi-taper spectral analysis was used to perform vocalization classification for laying hens in perch system. Sound Analysis Pro software was applied to compute spectral derivatives and acoustic features. Three methods including J48 decision tree algorithm, NaiveBayes theory and support vector machine were used to classify sounds of laying hens by using the open source data mining tool of Weka 3.6. Experimental results showed that vocalization of egg laying process and pleasure notes accounted for 42.2% and 21.6% between 7:00~8:00, while the natural behaviors and physiological activities were strongly performed with a comparison to traditional cage system. It was found that J48 decision tree algorithm had the highest classification rate (88.3%) for vocalization of laying hens, which could be used for different animal vocalization.