Every medicolegal investigation must include the identification of the individual. In terms of identification, fingerprints are thought to be the most precise and trustworthy sign. In criminal investigations and public safety cases like Law Enforcement, B. Legal Investigations, Social Security and Cultural Access, fingerprints are crucial. It also contributes to people’s lives being safe and comfortable. In order to accomplish this goal, the authors have conducted a thorough literature study that includes standard methods, processes, and algorithms for fingerprint-based gender recognition. Further, the authors have added a brief summary containing challenges experienced during the implementation of the existing system. It also includes the details of fingerprint features found in male and female fingerprints, and also summarizes several suggestions for gender segregation tactics. The proposed system offers advantageous techniques that include high speed, efficiency, precision, and capacity to decipher intricate patterns and pictures. Based on a person's fingerprint, we will be employing a convolutional neural network (CNN) to determine their gender, accomplishing the use of the CNN architecture, pooling layers and dropout design along with OpenCV.