Abstract <p>The use of certain research methods to determine the potential of a territory for certain types of minerals requires specialized software with mandatory compatibility with common types of data, support for major operating systems, and a simple graphical interface for comfortable operation by a wide range of users. In addition to research tools, the program should be able to save results in common file formats. The base surfaces method, based on topographic calculations with a detected erosion network, is used to identify the amplitude of relief uplifts and subsidences and to delineate local areas of neotectonic movements. In relation to predicting the mineral resource potential of the territory, the compiled maps of the orders of base surfaces and their difference maps in combination with other data sources make it possible to identify overlapping, potentially ore-bearing intrusions and placer sources. The study considers the ENOE 0.6a program and its application to analyzing ore-bearing structures of the Sikhote-Alin mobile belt with the example of gold placers in the territory adjacent to the Bekchiul multiphase pluton, which contains the large Mnogovershinnoe gold–silver deposit. With ENOE, a dataset was created describing neotectonic processes and the development of the erosion network. Based on the obtained materials, including geological, a predictive machine learning model was trained and tested, created using the maximum entropy method, which made it possible to outline known placer ore objects. Validation and application of the model to a control site demonstrated its efficiency as a preliminary analysis tool for the area.</p>