Biometrics involves the scientific and technological exploration of biological data from the human body. This entails capturing data, deriving distinctive features, and matching them with a template set in the database. Research indicates that single-mode biometric systems suffer from drawbacks in terms of performance and precision. In contrast, multi-modal biometric systems surpass their single-mode counterparts in performance, even when dealing with intricate scenarios. We assess the precision and performance of multi-modal biometric authentication through cutting-edge Commercial Off-The-Shelf (COTS) products. Our focus is on biometric systems centered around fingerprints and facial recognition, along with the decision-making and fusion techniques employed within these systems. The advantages of these multi-modal systems over single-mode. KEYWORDS: Authentication, Evaluation, Normalization Multimodal Biometrics, Fusion, face, fingerprint and Matching score.