The application of CSP (Constraints Satisfaction Problem) and CBR (Constraints-Based Reasoning) models for learning optimization and decision-making in educational environments in the field of gas distribution were analyzed. Calculations of training models were performed, which take into account all constraints and factors that affect the price of gas distribution. Educational cases were formed, which include such parameters as gas volume, temperature, pressure, level of consumption, availability of different types of consumers (commercial, industrial, household, etc.), tariffs and cost of distribution, constraints related to gas volumes, which can be supplied to a certain consumer in different periods of time, time constraints, requirements for quality and environmental friendliness of services. Using CSP and CBR approaches, the authors take into account all the constraints associated with gas distribution in economic and environmental aspects. The application of the CSP-CBR approach proposed by the authors can also be useful for adapting gas prices to changing conditions and the system can automatically adapt prices to ensure efficient and optimal distribution of gas for different categories of consumers and will ensure efficient use of resources from both an economic and an environmental point of view and for the projecting of relevant educational environments.