Assessing overhead line lifespan requires an overall knowledge of the environmental conditions that the conductors are subjected to and the correct treatment of human made observations that form the data set. These requirements have made it challenging to apply statistical learning, which calls for advanced machine learning techniques and needs to be supplied and reinforced by physical modelling. Here, we provide a methodology to assimilate data, then train and evaluate the appropriate models.