The Indian coastal belts boast several different types of crabs, out of which the Scylla olivacea (Orange Mud Crab) is more commonly occurring. The crabs are an intrinsic part of the marine ecosystem. It is important to maintain a balance of male and female varieties to conserve the marine bio-diversity. The crabs are also parts of many gastronomic fares all over the world. However, due to the difference in taste of the male and female crabs, it is important to identify them precisely before they are sold. The study of existing works in this domain revealed that not many works focused on Indian crabs. In this paper a new CNN method is employed to classify the gender of the crab. Firstly, the dataset was created by various methods of augmentation. Next a pretrained model was chosen to extract the crab image out of the entire image which contained a lot of background noise. The augmentation was performed on the extracted images to enrich the dataset. Next a CNN model was trained to these images. The results showed a 99.6% accuracy in the validation set and a 98.9% accuracy in the test set. A F1 score of 0.992 was achieved.