Personality prediction plays a key role in understanding human behavior, decision-making, and social interactions. The OCEAN model—comprising Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism is widely used for assessing personality traits. With the rise of machine learning, predicting personality using this model has become a growing interdisciplinary field. This survey paper reviews existing machine learning approaches, such as K-Means and Gaussian Mixture Models, used to analyze personality traits from questionnaire data. It also highlights the limitations of past studies, including lower prediction accuracy and challenges in model interpretation. The aim is to provide a clear overview of current methods and explore how machine learning can improve personality prediction and reveal deeper links between personality traits and behavior.