**6. Conclusions**

(1) The 3DMPM is an important tool for deep targets delineation for future exploration. This paper delineates five prospectivity targets with good mineralization potentials in the deep area of the Xuancheng–Magushan area, which can be used for future exploration.

(2) In the Xuancheng–Magushan area, the favorable areas divided by the random forest model contain 96.71% of known ore bodies and only account for 1.08% of the study area, which can show that the random forest model can perform better than the logistic regression model in the 3DMPM using the dataset of the study area. It means that the random forest model could provide more effective and accurate support for integrating predictive data during the 3DMPM.

**Author Contributions:** Conceptualization, F.M., X.L. and F.Y.; Methodology, F.M. and X.L.; Software, X.L.; Validation, X.L. and Y.C.; Formal Analysis, F.M., Y.C. and R.Y.; Data Curation, Y.C. and R.Y.; Writing—Original Draft Preparation, F.M.; Writing-Review & Editing, F.M., X.L. and F.Y.; Visualization, Y.C. and R.Y.; Supervision, X.L. and F.Y.; Project Administration, F.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by [National Natural Science Foundation of China] grant number [42072321], [National Natural Science Foundation of China] grant number [41820104007] and [National Key R&D Program of China] grant number [2016YFC0600209].

**Data Availability Statement:** Data not available due to legal restrictions.

**Conflicts of Interest:** The authors declare no conflict of interest.
