From the perspective of the complex demand for commanding and decision-making in modern electronic warfare, a quantitative aided decision-making model is established based on the dynamic inference ability of Dynamic Bayesian Network (DBN), and the one-dimensional quantitative analysis in traditional operation decision-making is transformed into quantitative, dynamic multi-dimensional analysis.The factors that have effect on the operation effectiveness are taken for building the BN at each operational moment.The dynamic inference of the auxiliary decision-making is realized by using HMM model inference algorithm based on the conditional probability matrix of the nodes.Simulation and analysis have been made to the actual exercise examples, and some practical and effective recommendations are obtained for commanding and decision-making of electronic warfare commanders, which demonstrates the effectiveness of the model.