Achieving sustainable practices in the jewelry industry necessitates the adoption of optimized eco-design approaches. The optimization of eco-friendly jewelry design was investigated in this study through an integrated analysis of materials, digital manufacturing, and predictive modeling. Sustainable techniques were identified, and an artificial neural network (ANN) model was developed to predict environmental impacts based on material properties and design attributes. The applicability of the model was validated, and insights were generated to drive eco-innovation and facilitate the transition towards sustainable practices in the jewelry industry. Key findings demonstrated the superior sustainability of renewable biomaterials, specifically Biomaterials 2-5 derived from lingo-cellulosic sources, compared to conventional materials. Consistently, simpler design configurations outperformed intricate designs. The relationships were effectively captured by the ANN model, providing a reliable evidence-based approach. Quantitative linkages between design attributes and sustainability metrics were established by the study, offering valuable guidance for optimization strategies. Significant results demonstrate that Biomaterials 2-5 exhibit average carbon footprints of 1.1–1.2 kg and water usage of 9–16.5 L, compared to 2.1 kg and 24.5 L for precious metals. Simplified designs exhibit carbon footprints of 0.8 kg and water usage of 11.5 L, whereas intricate designs show footprints of 3.1 kg and water usage of 33 L. These predictions establish renewable biomaterials and streamlined configurations as preferable paradigms for sustainable jewelry. Based on the findings, recommendations include prioritizing the use of Biomaterials 2-5 and streamlined configurations through the implementation of incentives. Transitioning operations towards biomaterial-focused infrastructure and emerging technologies is suggested to further enhance sustainability. Additionally, international cooperation and the development of standards are proposed to address sustainability challenges holistically. The empirical and computational findings of this study establish optimization methodologies that can inspire transformative sustainability practices in the jewelry industry.