Agricultural-related enterprises shoulder the vital mission of ensuring food security and stabilizing the supply of agricultural products. The implementation of the rural revitalization strategy and the vigorous development of new agricultural productivity have brought new opportunities for the transformation and upgrading of agricultural-related enterprises. However, the financial situation of agricultural-related enterprises in China is relatively fragile, and the construction of a scientific financial risk early warning model for agricultural-related enterprises is of great significance. Based on the financial data of 131 agricultural-related listed companies from 2018 to 2023, this article constructs a financial risk early warning model for agricultural enterprises based on BP neural network, and takes Beidahuang Agriculture Co., Ltd. as an example to verify the prediction results of the model. The research results show that the BP neural network financial risk early warning model for agricultural-related enterprises constructed in this study has relatively high prediction accuracy and can accurately identify the financial risk situation of agricultural-related enterprises. In the future, agricultural-related enterprises should promote the in-depth integration of intelligent financial early warning and digital management, continuously optimize the indicator system, and constantly enhance their technological innovation capabilities, risk prevention and control levels, and capital management capabilities, to drive the improvement of quality and efficiency and the transformation and upgrading of the enterprises.