Suburban rural areas of metropolitan regions can serve as the interface between urban and rural elements. Their rural settlements have posed challenges in recent years, such as idle and inefficient land use, scattered spatial layouts, and supply-demand mismatches in functions. Rural settlement consolidation can be expected to increasingly emphasize rural revitalization and territory-wide land consolidation. An accurate release of consolidation potential is often required for the precise alignment between land supply and development demand. Therefore, this study aims to assess the potential of rural settlements for the differentiated consolidation pathways in rural stock resources. A case study was taken of Jurong City, a suburb of the Nanjing metropolitan area. A "supply-demand assessment-type identification” framework was constructed using supply-demand theory. Supply–demand consolidation potential of rural settlements was also assessed using a one-class support vector machine (SVM) and machine learning. Furthermore, the precise pathways of land resource allocation were also explored at the village scale, according to the rural dominant function demands. The results show: 1) The theoretical consolidation potential of rural settlements was 8 490.19 hm², accounting for 61.51% of the settlement area. The willingness simulation model was validated with an accuracy of 87.81% and a recall rate of 95.48%, indicating high precision. The modeled willingness values ranged from 0.33 to 0.76 for administrative villages. Specifically, the villages with higher consolidation willingness were distributed in the southeastern region, including the Maoshan Scenic Area, Maoshan, Houbai, and Tianwang Town. The actual consolidation potential of rural settlements was 5441.91 hm² after correction, representing 39.42% of the rural settlement land. 2) The demand potential of rural revitalization ranged from 0.20 to 0.60, indicating a pattern of “higher in the west, lower in the east, with clustered distribution.” The number of medium-demand villages was the largest among all villages, totaling 100 (53% of all villages). 3) Four types of zones were identified for the supply-demand potential: priority consolidation, reserve regulation, demand-oriented, and stable control zone, accounting for 43, 35, 73, and 37 villages, respectively. 4) Four types of dominant functional demands were identified among the rural settlements, with the majority of balanced development villages. Most villages shared no dominant functional demand, resulting in a balanced functional profile with scattered spatial distribution. Potential zones were coupled with dominant functional demands. 12 consolidation types were derived at the village scale. Potential release pathways were summarized, such as “spatial reconstruction,” “precise guidance,” “flexible regulation,” and “micro-renewal,” thus enabling “one village, one strategy” precise intervention. Targeted consolidation measures were also proposed, such as “releasing potential through village reorganization” and “innovating dynamic land reservation supply.” Differentiated strategies were implemented to promote intensive and economical land use for the rural functions and spatial patterns. The findings can also provide a practical demonstration and reference to precisely match land supply with rural revitalization demands in the spatial units of metropolitan suburbs.