The problem of improving the efficiency of designing process of knowledge bases and expert systems remains a relevant issue. The effectiveness of this process can be improved by using the principles of conceptual (cognitive) modelling and generative programming‐based approaches, in particular, a model‐driven development. This paper describes implementation and application of the model‐driven development approach for the design of rule‐based expert systems and knowledge bases. The implementation proposed takes into account peculiarities of the intelligent systems development process, such as stages of conceptualization and formalization, and provides the practical use of ontologies and conceptual models as computation‐independent and subject domain models. An extension of UML, namely, the Rule Visual Modelling Language is used to represent logical rules and create platform‐independent and platform‐specific models. Rule Visual Modelling Language elements ensure that some features of a programming language for knowledge bases, for example, CLIPS, are taken into account. Therefore, CLIPS and the Personal Knowledge Base Designer are used as the targeted platforms for generation of source codes and specifications. The applicability of the approach is demonstrated by a case study: development of the knowledge base and expert system for identification of the causes of damages and destruction of construction materials in petrochemistry.

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