<p>The transition to a circular economy requires innovative frameworks that can identify, optimize, and visualize resource exchanges among industries. Industrial Symbiosis (IS), a key enabler of this transition, remains largely underdeveloped in Ghana due to inadequate digital ‘match-making platforms’, low awareness of IS, and data scarcity. This study presents a pioneering effort to simulate a theoretically constructed industrial symbiosis network (TCISN) using real-world data from 95 small and medium-scale enterprises across key industrial sectors in Ghana. A combination of geospatial analytics, network theory, and optimization algorithms were used to model and visualize waste-to-resource exchanges through a digital, GIS-enabled interface. The TCISN reveals scale-free topologies with key hub industries such as cement, metal smelting, agro-processing, manufacturing and recycling sectors driving material recovery through highly connected exchanges. Slag, carbon black, aluminium and steel scraps, palm kennels emerged as the most frequently exchanged by-products, suggesting strong potential for material reuse. Spatial clustering, centrality analysis, and community detection further identified high-synergy zones and underutilized resource flows. The TCISN indicates a moderate level of circular integration, recording a system-wide circularity potential of 0.43. The findings provide a replicable model for circular industrial development in emerging economies, underscoring the viability of a data driven IS platform tailored to the Ghanaian context. They demonstrate the potential of digital matchmaking systems to enhance circularity, inform policy, and guide sustainable industrial planning. This pilot model offers a foundational blueprint for developing an operational IS tool in Ghana and may catalyze broader systemic shifts toward resource-efficient industrial ecosystems. </p>