Personality, a person’s distinctive way of thinking, behaving and feeling is an important aspect that makes up an individual and sets them apart from others. In today's world, understanding personality is vital particularly in cases where educators and trainers struggle to recognize the abilities and qualities of each student. This issue stretches beyond a superior-subordinate relationship and is also prevalent in interpersonal relationships, where individuals often fail to understand their partner's character. To address this issue, a machine learning model that helps determine an individual’s personality based on scores provided by an analyzer from their perspective with regards to Introversion, Judgement, Sensing and Thinking abilities has been developed, using MBTI framework with scores ranging from 0 to 10. The model also takes into account an individual's area of interest, gender, education level, age to analyze how external factors can influence an individual’s personality. Using this comprehensive set of features, an XGBoost model is employed to analyze inputs thus, providing a robust and data-driven approach in predicting an individual’s personality. An accuracy score of 90.28% and an overall precision and recall value of 0.86 acts as a testament to the model’s efficient performance across all classes. Furthermore, it offers compatibility insights with other personality types, which can help enhance interpersonal skills among different personalities and a conjoint user interface that simplifies the interaction with the model. This solution aims to enhance professional and personal relationships of individuals by fostering better communication and understanding leading to a profound growth in their lives.