When the transmission tower foundation in landslide area is displaced, the maximum displacement of the tower and the maximum stress of the rod will change. The state prediction model of the tower can be established to obtain the maximum displacement of the tower and the maximum stress of the rod, so as to prevent the occurrence of disaster accidents. Proposes an improved sparrow search algorithm to optimize the prediction model of BP neural network. Firstly, Sin chaotic sequence and the dynamic adjustment strategy of step factor are used to optimize the sparrow search algorithm. Secondly, the optimized model is used to optimize the weights and thresholds of BP neural network to obtain the prediction model. The displacement value of the tower foundation in the direction XYZ is taken as the input of the prediction model, and the maximum displacement value of the tower and the predicted maximum stress value of the tower members are obtained. Compared with the model of BP neural network, the root error RSME value decreased by 63.4%, the average relative error MAPE value decreased by 60.4%, and the absolute mean absolute error MAE value decreased by 62.6%. At the same time, the predicted value of the prediction model in this paper was in line with the changing trend of the real value. In conclusion, the prediction model can accurately predict the operation state of the transmission tower and provide strong guarantee for its safe operation.