The Sustainable Development Goals (SDGs) encourage sustainable practices in organisations opting to use renewable energy resources. The current study focuses on the development of a framework for the adoption of Industry 4.0 technologies (I4.0T) and Circular Economy (CE) practices that can help to achieve the SDGs for the manufacturing sector. The I4.0T-CE practices and the performance metrics were identified from the literature. The Pythagorean fuzzy analytical hierarchy process (PF-AHP) was used to compute the weights of the 30 identified I4.0-CE practices and the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method was used to prioritise the 18 performance metrics. The PF-AHP and the PF-CoCoSo are the advanced computational methods used in multicriteria decision analysis. The data was collected from 15 experts of Indian manufacturing industries. The industrial expert panel was asked to provide their input through a pairwise comparison matrix. The analysis of the results shows that the top three I4.0-CE practices are “Reduced”, “Collaborations and Partnerships” and “Continuous Improvement”. In contrast, the top three performance metrics are the “No. of global policy measures”, “No. of government budget appropriations” and “No. of innovation using low carbon technologies”. The study contributes to industrial practitioners in implementation, and researchers in theoretical enhancement. The performance metrics enable tracking progress, identifying improvement areas, and making informed decisions for achieving SDGs.