One of the most important aspects of computer vision and machine learning nowadays is gender detection through picture recognition, which has profound consequences for practical applications. This study uses the powerful InceptionV3 model to explore, build, and evaluate gender detection algorithms that are particularly applied to photos. The main goal is to examine the InceptionV3 model’s accuracy and effectiveness after being trained on a variety of datasets, so illuminating its practical implications. An extensive review of developments, approaches, and difficulties in the field of image recognition and gender detection is provided in the literature review that serves as the foundation for this study. The flexibility of the InceptionV3 model and dataset in the context of gender categorization tasks is clarified with particular attention. The goal of this thorough method is to offer insightful information that advances knowledge of gender detecting systems.