Engineering systems, such as aircrafts, hydraulic, electronic and electrical systems are becoming more complex and are subjected to failure modes that impact adversely their reliability, availability, safety and maintainability. In particular, hydraulic systems are challenging from the condition monitoring point of view due to the non-linear equations that describe behavior of the fluid. For this reason, numerous efforts have been made to improve the reliability of hydraulic system, leading to the development of complex algorithms for diagnostics and prognostics. In the present research, both diagnostic and prognostic algorithms have been developed, considering the case of an hydraulic crane available at the Purdue's Maha Fluid Power Research Center.