Abstract: Skin cancer is one of the cancers, which is not prominent and considered much like other cancers. Malignant melanoma is the third type or stage of skin cancer which leads to death. It can be prevented only when it is detected at a very early stage but that’s the challenging task in melanoma diagnosis. Most of the clinicians are familiar with Asymmetry, Border, Color and Diameter (ABCD) analysis to predict and diagnose the melanoma. Asymmetry plays a major role and it will be one of the best indicators to confirm the presence of cancerous melanocytes. When the images of melanoma skin lesions are subjected to preprocessing and it is investigated with the help of emerging techniques such as Evolutionary Programming, Fuzzy Logic, Artificial Neural Networks and Genetic Programming and Algorithms, it will provide better assistance for the clinicians to predict the melanoma at a very early stage. The study presents a review on various soft computing techniques that exist in the literature to identify the asymmetricity of the melanoma skin lesions with more precision.