Traditional persona classification methods rely on static, time-consuming techniques like surveys and interviews. To address this limitation, we propose F2, a novel approach that leverages facial recognition and digital footprint analysis for dynamic persona classification. By integrating real-time data from various digital platforms, F2 creates more accurate and up-to-date user profiles. Our system prioritizes user privacy and adheres to relevant data protection regulations. Through robust facial recognition and advanced machine learning algorithms, F2 effectively categorizes users into distinct personas, enabling tailored experiences and personalized interactions. This innovative approach has the potential to revolutionize user modeling and enhance digital experiences across diverse domains.