This article examines the issue of creating a rule-based question-andanswer system in the Uzbek language aimed at automatically responding to
questions arising during the admission process to higher education institutions (HEIs). The system processes users’ questions by normalizing their
morphological forms (lemmatization) and identifies appropriate answers based on rules. Drawing on questions related to the admission process in HEIs, the system covers more than 400 questions regarding application procedures, document requirements, and examination formats. The system’s software was developed using the Python programming language. The Jaccard similarity method was employed to find matching questions. The article provides a detailed discussion of the system’s architecture, rule base, and answer generation mechanism, while also evaluating its effectiveness and exploring possibilities for hybrid approaches in the future.