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Post-earthquake reconstruction involves complex decision-making that extends beyond structural safety to include economic, environmental, and social considerations under conditions of uncertainty and limited resources. Although sustainability-oriented assessment frameworks and multi-criteria decision-making approaches have increasingly been applied in disaster contexts, existing models typically address localized technical interventions and rarely support strategic reconstruction planning after earthquakes. This study develops a sustainability-based decision-support framework for post-earthquake reconstruction of reinforced concrete buildings using the Integrated Value Model for Sustainability Assessment (MIVES). This framework is derived through a systematic synthesis of the post-earthquake, post-disaster, and MIVES-based literature. Reconstruction alternatives reported in previous studies are first identified and classified to structure the reconstruction decision space. Sustainability requirements, criteria, and indicators are then examined and adapted through processes of retention, modification, elimination, and addition. The principal outcome of the study is an adapted MIVES requirements tree composed of 10 criteria and 19 indicators organized across the sustainability dimensions, providing a context-consistent hierarchical structure for strategic building-level reconstruction decisions. By explicitly linking reconstruction alternatives with sustainability indicators within clearly defined decision boundaries, the framework strengthens methodological rigor in sustainability-oriented reconstruction planning. The present article focuses on the methodological development of the framework (Part I). The operational implementation of the model—including expert-based weighting, value-function definition, indicator aggregation, and empirical validation through case studies—will be presented in a companion study. The proposed framework provides a transparent and transferable basis for sustainability-oriented reconstruction planning and supports informed decision-making by public authorities.