Anti-missile firepower distribution is one of the key tasks of BM, the firepower distribution model and the efficiency of solving it affect the result of the anti-missile defense warfare directly. The research on anti-missile firepower distribution is done, and the model of anti-missile firepower distribution is built. This paper presents a continuous Hopfield neural network-based algorithm for the optimization of the anti-missile firepower distribution and analyzes the convergence and stability. Finally, three representative examples are solved by the method presented in this paper, and the numerical results are present.