The overarching aim of this project is to develop a next generation data infrastructure linking farm-management, genetic-improvement and traceability. The objective here is to prove feasibility of using image analysis, particularly latest advances in deep learning, for parentage assignment in livestock using sheep as an exemplar. For example, given we have a facial image from a lamb and multiple pictures of possible fathers (rams) and mothers (ewes) the goal is to correctly identify the parents of this lamb. Rather than requiring manual identification of phenotypes for each new sheep, we aim to create and train a convolutional neural network (CNN) model capable of detecting features for matching parents with their offspring directly from images of animal faces.