<p>The concept of sustainable development goals is so crucial to guiding nations toward a more sustainable and equitable future. This research project is primarily focused with anticipating and improving India’s trajectory toward reaching the sustainable development goals targets through the use of Bayesian structural time series and fuzzy optimization techniques. To examine the trends, projections, and uncertainties of chosen sustainable development goal indicators, Bayesian structural time series are utilized to model the target time series data. The Bayesian-based Bayesian structure time series framework allows for the integration of prior information as well as the assessment of uncertainty when modeling and predicting time series data for sustainable development goal indicators. This Bayesian technique enables probabilistic forecasting, which is crucial for comprehending the range of potential future outcomes in the face of uncertainty. To address any differences and ambiguity in the obtained data, the notion of fuzzy goal programming is applied, allowing for a clear assessment of goal attainment and the identification of major areas for development. The integrated technique not only improves the measurement precision of the sustainable development goals, but it also aids in understanding the trade-offs and complementarities between key sustainable development goals indicators. The study validates the effectiveness of the given hybrid strategy in providing vital information for strategic and policy choices for India’s sustainable development.</p>