This work explores the fusion of dermatoglyphics and deep learning to create a hypothetical model for individualized learning and career guidance. Dermatoglyphics, the scientific measurement of fingerprint patterns, has been linked with neurodevelopment and cognitive abilities. This paper introduces a deep learning model that utilizes dermatoglyphics (fingerprints) to ascertain cognitive traits, which are then correlated with learning habits and relevant professions. Employing the capability of deep learning, this work proposes an AI model to recognize fingerprint traits and determine brain dominance. The model aims to achieve objective and scalable cognitive profiling, maximizing educational planning and career guidance based on innate cognitive strengths. Fingerprint image acquisition, preprocessing, brain dominance through deep learning-based classification, and an AI-based recommendation system for career advising are the proposed methodology steps. This current methodology proposes a non-invasive, data-driven solution for assessing brain dominance. Ethical considerations, data privacy, and the need for substantial empirical validation are, however, pertinent issues to be resolved. This model has the potential to change individualized learning and career planning through the fusion of biometrics, artificial intelligence, and cognitive neuroscience, subject to its establishment through large-scale research.