Every year, in India, large number of children are reported for missing. Among them, many children are gone undetected. Various NGOs are formed to deal with the missing children issue. Even though, many researchers are working on this particular area. In this chapter, we used the deep learning methodology for identification of missing children from the available photos by using the facial recognition. The convolutional neural network (CNN) and multiclass SVM are the base concepts in this model. CNN, a very successful deep learning technique, is incorporated for face recognition. By using a pretrained CNN model VCG-Face deep architecture, facial description of images is extracted. The CNN is used to extract the facial description of images and SVM is responsible for face recognition. Choosing the best CNN VGG-Face models for face detection and proper training of it results in a DL model difference to noise, illumination, contrast, occlusion, image still, and age of the child, and it out performs the results produced by this mode. Initial methods in face recognition based missing child identification. Performance achieved for child identification system is 99.41%. It’s a huge percentage, and it was evaluated in most number of child missing cases.