This chapter provides a survey of the diagnosis and prognosis methods provided in literature, as well as those of technical proximity, eg., conditioned-based maintenance, prognostic health management, fault detection and isolation, and structural health monitoring. After a positive diagnosis of impending fault or failure in the engineering system or process, prognosis takes place and provides ample time for rectification before total breakdown or instability. Parametric-based methods for diagnosis and prognosis are attractive because the underlying physics or statistics can be captured and understood. The chapter discusses the novelty of the proposed methodologies and the application to realistic industrial networked systems. It investigates power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches, and identifies those parameters that have great impact on system eigenvalues, therefore, the system stability properties. The chapter presents a framework of probabilistic power system small signal stability assessment technique, fully supported with detailed probabilistic analysis and case studies.