The present paper discusses the use of a Kalman filter-based method to identify fall events during rock climbing activity. The proposed technique relies on the acquisition of three-axis acceleration and altitude by means of a data logger integrated within the climber’s sit harness. Time-domain results exhibit the working principle of the algorithm. Furthermore, the data provided by eight climbers is analysed and discussed to validate the method.