This article addresses the issue of formally representing algorithmic knowledge in computer science through the modeling of algorithms in the form of ontology. The main goal of the study is to structure algorithmic concepts and adapt them for use in information systems, artificial intelligence, and the educational process. The methodological framework relies on the widely recognized Protégé ontology editor and the OWL (Web Ontology Language). In constructing the ontology, the “Algorithm” class was chosen as the core, with subclasses identified as SortingAlgorithm, SearchingAlgorithm, GraphAlgorithm, OptimizationAlgorithm, CryptographicAlgorithm, and MachineLearningAlgorithm. Object properties such as hasComplexity, hasDataStructure, hasApplication, usesAlgorithmType, and hasStep, as well as data properties including hasName, hasTimeComplexity, hasSpaceComplexity, hasAuthor, and hasYearIntroduced were defined. These properties make it possible to describe algorithms in terms of efficiency, application domains, and historical context in a formalized manner. The results demonstrated that structuring algorithmic knowledge within an ontology not only enables automated processing but also improves its practical application in education, artificial intelligence, semantic web technologies, and intelligent information systems. The developed ontology provides a new level of formal knowledge representation in informatics and serves as a foundation for further expansion and adaptation to specific applied domains.