To address the practical problems in the prediction and assessment of cyberspace state, this paper studies the prediction of variables in cyberspace, and presents a state prediction method based on Non-Homogeneous Dynamic Bayesian Networks (NH-DBNs), so as to solve the problems in the existing model of single time-sequence regression and the ignorance of the inter-influence between multiple variables.The presenting form of the network state is given, and the method and process of state prediction are presented. The comparison experiment conducted in the same environment has proved that the algorithm accords with the practical application environment, and can improve the prediction accuracy of the indexes of the cyberspace state. The algorithm has certain value for the conductor to make scientific, reasonable and accurate decisions.