In various industrial applications such as transport, automotive, marine, diesel motors are widely used. However diagnosing faults and/or predicting its future health condition of such motor still remains widely open due to its complexity from both structural and functional points of view. The paper presents a study on health state prediction of such industrial diesel motor. A particle filter-based prognostic is developed and applied from real recorded data with different measurements. The recorded data are firstly pre-processed, and health indicator is then chosen before implementing the proposed approach. The use and advantages of the proposed approach are then highlighted through the obtained results.