Network design is a critical topic in supply chain management, integrating forward and reverse flows to create a closed-loop supply chain (CLSC) network. In the tire industry, CLSC networks must strategically address facility location and allocation across multiple levels, including suppliers, manufacturers, retailers, and markets for forward flows, and collectors, recyclers, and secondary markets for reverse flows. With the rapid growth in demand for tire manufacturing, existing CLSC networks often fail to meet the escalating of demand satisfaction, necessitating a comprehensive redesign to enhance facility location and capacity planning performance. This paper proposes a novel framework for redesigning CLSC networks in the tire industry by formulating a mixed-integer programming (MIP) model that incorporates unique challenges specific to network redesign. Most importantly, the network design for the CLSC differs significantly from the CLSC network redesign. In the latter, facilities are divided into two subsets: a set of open facilities and a set of candidate facilities. The decisions involved not only pertain to the opening of candidate facilities but also to the closure of existing open facilities, while balancing the varying fixed and variable costs associated with these transitions. The developed MIP model for the network redesign problem explicitly accounts for these decisions, providing a practical tool for addressing real-world complexities within the CLSC for the tire industry. Extensive sensitivity analyses are conducted to evaluate the impact of key parameters, such as network redesign costs and recycling efficiency. The results help the CLSC networks to optimize their CLSC to achieve higher efficiency and better demand satisfaction. This research not only highlights the importance of network adaptability but also provides an efficient decision-support tool for redesigning CLSC systems in high-demand industries.