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Microbial abundance and community structure can be altered directly and indirectly by soil physical and chemical characteristics which, in turn, can be influenced by land use management. This study utilized the cubist model to predict soil microbial communities based on soil properties at different depths and under different agricultural management in Dawson County, Montana, USA. A total of 538 soil samples were collected from three management treatments (control, no-tillage (NT), and no-tillage with livestock grazing in winter (NTLS)) from three depths (0–5, 5–15, and 15–30 cm). Soil physical and chemical properties and total phospholipid fatty acid (PLFA) analysis were used to predict soil biological properties. Root mean square error (RMSE), mean absolute error (MAE), relative error (RE), mean bias error (MBE), and R squared (R²) were used to assess the performance of predictions. Results showed that …