The study is aimed to estimate the possibility of using machine-learning method “Random Forest”, to obtain a probabilistic estimate of the distribution of an oil-saturated reservoir. The object of research is the Achimov complex, composed of relatively thin interlayered terrigenous rocks. The “random forest” method realized with the scikit-learn Python library of the. Application of the algorithm converts the input cubes of elastic parameters to probability cubes of lithotypes, which used for geological interpretation. As a result, the trends of reservoir properties estimated, as well as the probability cube of an oil-saturated reservoir. These data can be effectively used in planning the well-paths.