A deep neural network approach to facial recognition and identification leverages advanced architectures like Convolutional Neural Networks (CNNs) to analyze and distinguish facial features with high accuracy. By training on large datasets of facial images, these networks learn to extract and encode distinctive features, enabling them to recognize and identify individuals even in varied conditions. This method significantly enhances performance in real-world applications, such as security systems and user authentication, by providing reliable and scalable solutions to face recognition challenges.