This study investigates the integration of digital twin technology in the design of traditional cultural and creative products, addressing the challenges of innovation and efficiency in the cultural and creative industries. By employing digital twin network modeling, we develop an intelligent design method that digitally replicates and optimizes cultural products, enhancing design efficiency and innovation. Our approach involves digital modeling of traditional characteristics through preprocessing and feature extraction, followed by multi-scale design evolution experiments in a virtual environment. Results show a 30% improvement in design efficiency and increased product innovation and user satisfaction, demonstrating the method’s potential to revolutionize traditional product design while preserving cultural essence. This research contributes to the intelligent design of cultural and creative products and suggests new avenues for the cultural industry’s innovative growth.