An animal’s behaviour can be a clear indicator of their physiological and physical state. Therefore as resting, eating, walking and ruminating are the predominant daily activities of ruminant animals, monitoring these behaviours could provide valuable information for management decisions and individual animal health status. Traditional animal monitoring methods have relied on human labor to visually observe animals. Accelerometer technology offers the possibility of remotely monitoring animal behaviour continuously. In terms of commercial reality, an ear-borne sensor is the most suitable for the sheep industry. The aim of this study was to determine the effectiveness of an eartag deployed accelerometer sensor to differentiate between, grazing, standing and walking behaviours from a Merino ewe. Using a subset of eight summary features a Quadratic Discriminant Analysis (QDA) correctly predicted 100%, 83% and 100% of grazing, standing and walking events respectively. Preliminary results are promising and indicate that an ear-deployed accelerometer is capable of identifying the key sheep behavior’s that might contribute to disease detection and welfare validation. Further research is required to assess the suitability of accelerometers for behaviour detection across different sheep ages, breeds and environments.