ABSTRACT
This study examined whether MBTI personality types and CliftonStrengths themes could predict academic major indecision in 177 undergraduates using random forest classification and K-means clustering. The model achieved strong predictive performance (accuracy = 88.9%, macro F1 = 0.88), with lower ranked strengths (Strengths 4 and 5) emerging as the most influential predictors. Clustering identified three distinct strength profiles; students in the execution-dominant cluster were significantly more likely to have declared a major, whereas influence-oriented or diffuse profiles were associated with indecision. These findings support the use of strengths-informed modeling for the early identification of students who may benefit from targeted academic advising.