SUMMARY
Since most chemical processes are catalytic; the problem of the choice of catalysts is traditionally considered in many publications and is covered on many Internet sites. In this paper; the catalytic process of methane oxidative condensation and intelligent technologies for analysis and decision making for choosing the best catalyst option are considered as an object of research. The authors of the work consider many literature and Internet sources; which highlight the problems of the choice of catalysts in general; and indeed for the methane oxidative condensation. As a result of studying numerous sources; the authors determine that the tasks associated with choosing the best catalyst in each case are often very ambiguous and complex. Therefore; any informational support in solving problems related to the choice of catalysts will be useful. A large amount of information; the attraction of modern computer technology and the knowledge of qualified experts; all this makes the creation of an intelligent decision support system an important and real task.This work is aimed at developing an intelligent decision support system to select the most effective catalyst for the methane oxidative condensation.The methods chosen in the decision-making system are the hierarchy analysis method and data mining based on decision trees. The first of them requires the participation of a human expert; the second performs data mining without the participation of a specialist. It should be noted that the choice of the latter is also due to the fact that methods based on decision trees are among the top ten in terms of their effectiveness for data mining.For computer implementation of the system; object-oriented programming based on Microsoft Visual Studio is used.In the course of the study; in addition to the choice of catalysts using the developed decision-making system; a computer simulation of the methane oxidative condensation using the selected catalysts is carried out and the best version of the scheme is chosen. The obtained results can be useful at the design and implementation stages of the corresponding production; as well as used by process operators to analyze the production process.