<p>A significant share of rural residences in China exhibits inadequate thermal insulation and elevated levels of carbon emissions. Meanwhile, the economic cost constitutes a crucial determinant for achieving the renovation. In this study, the incremental cost, life cycle economic benefit and environmental benefit models were developed involving a market price prediction of building materials used in the renovation of existing rural residences. Furthermore, the renovation of existing rural residences was optimized using a multi-objective method, which incorporated global sensitivity analysis, surrogate model development, and the selection of an optimization algorithm. Finally, an optimal set of design parameters was derived through using the weighted TOPSIS method. Interestingly, the optimal design parameters were compared for the renovation of existing rural residences under the different remaining service lives. The result indicates that the insulation type of roof has the highest first-order sensitivity index and global sensitivity index for the life cycle economic benefit, CO₂ emission reduction, and predicted percentage dissatisfaction, while that is the lowest for the type of window. Interestingly, longer remaining service life tends to promote the adoption of windows with better thermal insulation performance. The renovation of existing rural residences with shorter remaining service life is more worthwhile across the board, despite that has the greatest life cycle economic benefit under the remaining service life of 40 years. Overall, prioritizing roof insulation and optimizing window choice based on service life are key strategies for improving the renovation benefit of the existing rural residences.</p>