Abstract: In this paper,the specific values of the ink transferring ratio was predicted according to the data of its influential factors by using neural network. RBF neural network was selected as the model of prediction network by comparing the radial basis function( RBF) neural network,Elman neural network and back propagation( BP) neural network. The main influence factors of ink transferring ratio were determined according to the correlation among the various factors and their impact on the ink transferring ratio. Considering the main influencing factors,a group of experiments were taken by using orthogonal experimental design and uniform design experimentation,and the result was used as the sample data of the neural network. The RBF neural network was trained by the sample data,which enable the network to predict the ink transferring ratio under different factors.Resultsshow that the predicted value of RBF neural network is more accurate than Elman neural network and BP neural network through contrastive analysis.