Soil quality assessment is crucial for understanding soil heterogeneity and guiding appropriate agricultural practices. This study selected optimal soil indicators and MDS in the black soil area of Jilin Province, comparing different scoring methods, indicators and datasets to clarify soil quality spatial distribution characteristics and their relationship with environmental factors. Firstly, the IDS of soil indicators was screened via the correlation between yield and soil indexes. Then, PCA was used to select the MDS of the IQI derived from the LS method as the optimal evaluation model for assessing soil quality in the study area. The MDS included BD, SOM, AN and AK. The results showed that soil quality was mainly moderate (Grades II, III, IV), accounting for 70.28% and 78.38% of IDS and MDS, respectively, with IQI gradually increasing from northwest to southeast. Finally, environmental factors were integrated to analyze key drivers of regional soil quality differences: in the EHM region, the main influencing factors (in descending order) were Pre, TWI, Temp, Slope and PM; in the CEH region, they were Pre, Slope, PM, TWI and Temp; in the WSP region, they were Temp, TWI, PM, Pre and Slope.