The detection of degradations and resulting failures in electronic components/systems is of paramount importance for complex industrial applications including nuclear power reactors, aerospace, automotive, and space applications. There is an increasing acceptance of the importance of detection of failures and degradations in electronic components and of the prospect of system-level health monitoring to make a key contribution to detecting and predicting any impending failures. This paper describes a parametric system identification-based health-monitoring method for detecting aging degradations of passive components in switch-mode power converters (SMPCs). A nonparametric system response is identified by perturbing the system with an optimized multitone sinusoidal signal of the order of mVs. The parametric system model is estimated from nonparametric system response using recursive weighted least-square (WLS) algorithm. Finally, the power-stage component values, including their parasitics, are extracted from numerator and denominator coefficients based on the assumed Laplace system model. These extracted component values provide direct diagnostic information of any degradation or anomalies in the components and the system. A proof of concept is initially verified on a simple point-of-load (POL) converter but the same methodology can be applied to other topologies of SMPC.