Advanced biometric verification has attracted much attention in an age when security and personal identification have become of prime importance. With rapid advancement, the need for strong authentication systems developed that use unique physiological characteristics. One of the promising approaches is the application of the Fast Fractional Fourier Transform algorithm. The fast fractional Fourier transform algorithm explores how the Fourier transform can enhance the biometric verification processes, especially retina authentication. This technique provides a unique ability to process retina images in a time-frequency domain by using the FFrFT, which generalizes the conventional Fourier transform. Biometric verification technology using retinal images for the purpose of authentication is one of the most used today. This paper proposes a new method of retina verification by using the FFrFT Algorithm to verify the retina. The fractional Fourier transforms can be compared to distinguish whether the retinas are coming from the same individual by comparing the FFrFT of two retinas. The algorithm is designed to increase the efficiency and accuracy of biometric systems by transforming fingerprint data into the frequency domain, hence allowing better feature extraction and recognition capabilities. In comparison, FFrFT shows better performance than traditional methods by effectively managing the variable frequency nature of biometric signals. Consequently, this approach enhances the reliability of identity verification systems and addresses challenges associated with noise and distortion in biometric data. In general, the use of the fast FFrFT algorithm means a huge step toward biometrics, since it provides an efficient solution for secure and efficient identification systems.