This study aims to establish a data-driven decision framework for selecting natural rubber (NR) in aviation tire formulations, in order to overcome the problem of long-term reliance on empirical knowledge and enhance the ability to autonomously select materials for high-end equipment. A multi-dimensional simulation performance database was constructed, covering six mainstream NR brands from six major production areas, namely Malaysia (MYS), Indonesia (IDN), Thailand (THA), Vietnam (VNM), Hainan (CHN), and Yunnan (CHN), which were selected based on market dominance and traceability in the literature. This database integrates the raw material rubber composition, molecular parameters, and static or dynamic mechanical properties of the vulcanized rubber. Grey Correlation Analysis (GRA) was introduced as the core decision model. By calculating the grey correlation grade between each NR brand and the ideal reference sequence based on the target performance indicators, the multi-criteria ranking of different functional components of aviation tires (such as tread, shoulders, sidewalls, and carcass) and differentiated material recommendations were achieved. To verify the reliability of the model, it was first applied to the mature main landing gear tires of the Boeing 737-800 aircraft, and the model output results were compared with the material usage records of a well-known international tire manufacturer. In the verification case, Malaysia's SMR CV60 was determined as the optimal choice for the tread, shoulders, and sidewalls, and Vietnam's SVR 3L was the optimal choice for the carcass. Its performance fully matched the parameters of the ideal performance sequence, thereby confirming the reliability of the model. Subsequently, the validated model was applied to the main tires of the Chinese C919 aircraft. For the C919 main tires, the model recommended Malaysia's SMR CV60 as the best material for the tread, shoulders, and sidewalls, while SVR 3L demonstrated superior overall performance in the carcass composite material. This framework provides a scientific material selection basis for the C919 main tires, reveals the potential for substitution of domestic NR materials in specific tire components, and offers a transparent and quantifiable alternative solution for the decision-making of high-performance tire formulations, replacing the traditional empirical decision-making. Its innovation lies in combining the specially constructed performance database with GRA (tire formulation analysis system) to achieve a data-driven decision-making method. It provides the first data-based natural rubber selection suggestion for the C919 main tires and systematically demonstrates the feasible ways to substitute domestic natural rubber in key aviation components.