The paper presents a comparative analysis of two widely used decision-support approaches under conditions of uncertainty: correlation and regression analysis and expert assessment methods. Their methodological foundations, advantages, limitations, and areas of application in higher education are examined. Particular attention is devoted to the application of the expert assessment method for evaluating students’ judgments regarding the factors influencing the educational process. A practical study was conducted using survey data collected from undergraduate students enrolled in six educational programmes at Lviv University of Trade and Economics: ‘Computer Science’, ‘Management’, ‘Tourism’, ‘Logistics and Trade’, ‘Business Advertising’ and ‘Law’. The ranking method was applied to determine the priority factors affecting students’ educational activities, while Spearman’s rank correlation coefficient and Kendall’s coefficient of concordance were used to evaluate the consistency of students’ judgments across different fields of study. The results demonstrate that the need to combine study and work represents the highest-priority challenge shared by students across the analysed programmes, whereas insufficient educational and methodological support was identified as the least significant factor. The comparison of students’ evaluations revealed both common university-wide priorities and programme-specific differences reflecting the characteristics of individual disciplines. The study confirms that expert assessment methods constitute an effective tool for analysing educational processes in situations where statistical information is insufficient. The combination of expert evaluation techniques with quantitative statistical approaches provides a more comprehensive basis for decision-making and supports the development of evidence-based strategies for improving the quality of higher education.