Due to the rising number of users especially in platforms like Facebook, YouTube, Instagram, and so on, automated classifying of age and gender detection has a lot of importance in this era. To implement this technology, the model is designed by detecting the age and gender of a person in separate entities to avoid confusion. Here deep learning algorithm convolutional neural network (CNN) has been used to address this problem. The OpenCV algorithm has also been used with a pre-trained Caffe model for age and gender detection. This model has the ability to identify numerous faces in a single image and forecast the gender and age of each face. The research paper showcases the rationale behind the selection of Caffe as the framework model over alternatives such as HAAR Cascade. Additionally, it presents empirical evidence indicating that the integration of OpenCV with Caffe Model yields superior outcomes compared to utilizing TensorFlow in conjunction with other models. From the 100 sample images that were taken for evaluation, an overall accuracy of 87% was achieved.