The water-energy crisis seriously affects the sustainable development of China's steel industry chain. To achieve a coordinated development new path from the perspective of circular economy, it is necessary to analyze “water-energy-economy” dependency relationship of the steel products. This study analyzes a variety of steel products from the perspective of industry chain and simulates the “water-energy-economy” potential changes of products under different scenarios by developing a multi-objective optimization model. In this model, Random Forest (RF) and GEne Network Inference with Ensemble of trees (GEINIE3) algorithms are combined to evaluate the 2013–2019 “water-energy-economy” dependency relationships firstly. Then, improved Quantum Particle Swarm Optimization (QPSO) algorithm is applied to dynamically simulate potential changes of water, energy and economic performance in the steel industry chain under different scenarios, and to design an optimal development path from the perspective of optimizing economic performance within minimum water and minimum energy use constraints. Results firstly point out the current “water-energy-economy” triple dimension dependency relationship of China's steel industry is weak. Secondly, the “water-economy” dependence has changed from one-way dependence to two-way dependence, and the “energy-economy” relationship still shows a one-way dependence. Finally, when improving resource utilization rate, assigning priority to the reuse of scrap steel, while restricting pig iron and primary steel use, may help maximize the coordinated development of “water-energy-economy” in the steel industry chain. Policy implications are proposed based on the results and provided decision-making basis for the country and relevant enterprises to promote sustainable development of the steel industry chain.