Renewing unused industrial buildings and landscapes has gained attention in academia and industry. Often clustered due to agglomeration effects and zoning, industrial sites form complex spatial systems across territories. Frequently polluted and located near key infrastructure, these areas faced decline and abandonment as economies transitioned to service-based models. Adaptive reuse of this “industrial heritage” offers cost-effective, sustainable solutions that preserve cultural and historical value. While significant projects can revitalize economically and demographically depressed regions, the lack of coherent spatial planning often leads to suboptimal outcomes when redeveloping sites individually. Despite increasing interest from both public and private sectors, decisions about site location, scale, and future use remain unclear. To address this, the paper proposes a replicable, context-specific, multi-scalar framework to identify optimal uses for sites within their broader industrial systems. Geospatial Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) are particularly effective, enabling the overlay and weighting of geospatial attributes to assess strengths and weaknesses. Once sites are scored, building-scale MCDA integrates technical and social analyses to determine optimal reuse strategies.