There are six neuronal control systems which are widely accepted as basic eye-movement patterns: Fixation system/ Saccadic eye movements/ Smooth-pursuit/ Vergence movements/ Vestibulo-ocular reflexes/ Optokinetic movements. Different subjects have different eye-movement performance in same or different tasks, so we try to analyze the daily performance through behavioral data of several macaques using machine learning algorithm, including parameters such as reaction time, duration, accuracy, amplitude, velocity, acceleration, pre-saccadic oscillations, post-saccadic oscillations. The results indicate that behavioral tendency of same macaque in different experimental tasks may represents one stable type of personality from the raw data to feature extraction and the final classification. In the same experimental task, macaques with different characteristics may have different response tendencies. In different experimental tasks, macaques with the same personality may have the same response tendency. Error trials will also be analyzed. This study attempts to obtain the quantitative estimation of personality through the Combination of the eyemovement data and the personality scale, providing a quantitative indicator for the psychological personality test. Meanwhile, the result may be used to assist in the diagnosis of ADHD, Autism, Parkinson’s disease and other diseases in human.