In order to objectively evaluate the wearing comfort of the lens.Eye movement data is collected using the eye tracker in experiments and the "changing percentage of eyelid spacing" is proposed as one of the evaluation indexes to evaluate the degree of wearing comfort. A new model to evaluate the degree of lenses comfort based upon the deep neural network is designed by combining the new index with other traditional eye movement indexes. The experiment results reveal that the proposed index of "changing percentage of eyelid spacing" is a good indicator in evaluating the degree of lenses comfort, and the deep neural network model has a high prediction accuracy and generalization ability. The research overcomes the disadvantages of the traditional fitting process which mainly relies on the subjective feedback from the patients, and therefore can effectively help optometrists and opticians to adjust the fitting plan objectively and accurately.