【Objective】Soil health is essential to achieving sustainable agricultural development. 【Method】 This study selected the soil of a typical rice-wheat rotation area in southern Jiangsu Province as the research object. By measuring physical, chemical, and biological indicators, principal component analysis was used to identify soil health indicators and determine their weights. Combined with the membership function, the soil health index was calculated and subsequently classified. The microbial community indicators were obtained via high-throughput sequencing, and the random forest model was used to screen the indicators and construct a soil health assessment system based on microbial community indicators. 【Result】The results showed that biochar application significantly increased the content of soil available phosphorus (AP), but the content of available potassium (AK) was slightly lower compared to direct straw returning. The impact of different treatments on the alpha diversity index of the fungal community was more significant compared to that of the bacterial community. Also, the minimum dataset for soil health evaluation in the typical rice-wheat rotation area in southern Jiangsu Province, selected based on principal component analysis, consisted of soil organic carbon, AP, AK, and the activities of SUC and urease. The application of nitrogen fertilizer, single straw returning, and straw carbonization returning significantly increased the soil health index, while double straw returning reduced the soil health index in the short term. Moreover, the microbial community indicators selected by the random forest model were the relative abundance of Spirochaetota, Actinobacteriota, Mortierellomycota, bacterial Chao1 index, fungal Shannon index, and the relative abundance of functional genes such as rbcL, nosZ, ureC, and soxA. 【Conclusion】 The results of this study provide a scientific foundation for the formulation of agricultural management measures in the southern Jiangsu region and offer valuable insights into the construction of a soil health system based on microbial community indicators.