In order to overcome the shortcomings of Euclidean distance measurement in face feature expression， a neural network face feature extraction model based on KL divergence is proposed.The convolution neural network is used to transform the input sample into a probability distribution.The distance between different samples is measured by the KLdi-vergence，and a cost function is defined to optimize the distance.The backpropagation algo-rithm is used to modify the parameters of convolution neural network，the network has a stronger ability to distinguish between facial features.The extracted face feature vector is transformed into neural network classifier to performs face validation with YouTube face database.The experimental results show that the method can not only improve the error rate but also improve the generalization performance.