To improve the efficiency of antenna modeling and change the problem of slow speed and low efficiency of traditional modeling methods, an antenna modeling method using improved butterfly algorithm ( BOA) to optimize multilayer feedforward neural network (back propagation neural network ( BPNN)) is proposed. Firstly, the BP neural network optimized by the butterfly algorithm is established with the multilayer feedforward neural network as the base network to solve the problem of low prediction accuracy of the BP neural network. Secondly, the beetle antennae search (BAS) algorithm is integrated into BOA, replacing the local optimization process of the butterfly algorithm with the beetle antennae search algorithm to reduce the spatial complexity of the BOA, solve the problem that the BOA is prone to fall into local minima, and create an improved BOA-BP neural network for accurate antenna modeling. The design example shows that the prediction accuracy of the network reaches 99. 60%, and the prediction error is reduced by 47% and 40. 9% compared with the traditional BPNN and the BPNN optimized by the unimproved butterfly algorithm, respectively. In addition, the running time of the improved BOA algorithm is reduced by 80. 86% and 82. 79% compared with the particle swarm algorithm and the genetic algorithm, which greatly reduces the running time cost of the network. In summary, the modeling accuracy and speed of the improved BOA-optimized BPNN are improved, which verifies the feasibility and effectiveness of the improved butterfly algorithm as a novel neural network optimization strategy.