Agroforestry is being promoted as a feasible land use management to improve understory economic benefits. However, there are few studies on species selection and the comprehensive evaluation of soil quality change in rhizoma bletillae (Bletilla striata) agroforestry systems. The soil quality index (SQI) and minimum dataset (MDS) methods can reflect the overall condition and were effective tools for understanding different cultivation systems. In this study, we evaluated the soil quality of four cultivation models (including three agroforestry systems: PeB, moso bamboo (Phyllostachys edulis)–rhizoma bletillae; PoB, plane trees (Platanus orientali)–rhizoma bletillae; CcB, pecan trees (Carya cathayensis)–rhizoma bletillae; and CK, rhizoma bletillae monoculture. The total dataset (TDS) consisted of 15 soil parameters containing physical, chemical, and biological characteristics. The results showed that soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) were finally selected and established as the MDS. Agroforestry could significantly influence soil quality. Compared with CK, the SQI in CcB significantly increased and decreased in PeB and PoB. Soil water content (SWC), nitrate nitrogen (NO3−-N), dissolved organic carbon (DOC), SOC, TN, and TP contents were higher in CcB than in the other cultivation models. Based on various soil indicators and SQI analysis, the CcB was the best in improving soil quality. These findings showed that the soil quality index based on the MDS can be used as an effective indicator for agroforestry systems selection. It provides theoretical guidance for the practice of bionic cultivation and the sustainable management of rhizoma bletillae.