In this research, machine learning methods and image processing will be utilized to determine whether a surface contains a deformity. Through the development of a C++ program to generate surface deformities given image length, width, maximum deformity radius, and sample size as the training set, we utilize machine learning classifiers, namely Convolution Neural Networks (CNN), Support Vector Machines (SVC), and K-Means Clustering (KMC) to classify surfaces with either no impact, low impact, medium impact, or high impact. This research can be directly applied to the defense industry in helping to determine the weak spots on vehicles, which may not survive enemy fire. Additionally, it can be used in the aviation industry in helping to detect airframe damage, which will aid in the determination of the flight-worthiness of aircraft and help maximize fuel usage. In turn, this platform can be utilized to speed up the process of identifying deformities, resulting in time and cost savings