This study provides a step-by-step analysis of closed-loop parametric system identification for DC-DC buck converter. In closed-loop parametric identification, input-output experimental data are used to estimate the transfer function coefficients of DC-DC buck converter. For system identification purpose, a high-frequency perturbation signal is injected in to the closed-loop system which acts as an input signal for identification experiment. Different input-output models such as Auto-Regressive eXogenous, Auto-Regressive Moving Average with eXogenous, output error, and Box-Jenkins are used to model the converter structure and prediction error method is used to estimate the parameters. Model validation schemes are used to validate the estimated model. Simulation and experimental analysis have been provided to validate the results obtained.