The mining industry annually consumes trillions of British thermal units of energy,a large part of which is saveable.Diesel fuel is a significant source of energy in surface mining operations and haul trucks are the major users of this energy source.Cross vehicle weight,truck velocity and total resistance have been recognised as the key parameters affecting the fuel consumption.In this paper,an artificial neural network model was developed to predict the fuel consumption of haul trucks in surface mines based on the gross vehicle weight,truck velocity and total resistance.The network was trained and tested using real data collected from a surface mining operation.The results indicate that the artificial neural network modelling can accurately predict haul truck fuel consumption based on the values of the haulage parameters considered in this study. The mining industry annually consumes trillions of British thermal units of energy, a large part of which is saveable. Diesel fuel is a significant source of energy in surface mining operations and haul trucks are the major users of this energy source. Cross vehicle weight, truck velocity and total resistance have been recognized as the key parameters affecting the fuel consumption.In this paper, an artificial neural network model was developed to predict the fuel consumption of haul trucks in surface mines based on the gross vehicle weight, truck velocity and total resistance The network was trained and tested using real data collected from a surface mining operation. The results indicate that the artificial neural network modeling can accurately predict haul truck fuel consumption based on the values ​​of the haulage parameters considered in this study.