This paper presents a rapid, non-destructive diagnostic method for transformer insulation aging based on terahertz time-domain spectroscopy (THz-TDS). Conventional approaches for monitoring key aging indicators, such as furfural and methanol in oil–paper insulated transformers, are limited by offline operation, labor intensity, and invasive sampling. Here, we describe a THz-TDS system capable of detecting and quantifying these chemical markers in transformer oil with high sensitivity and speed. Density functional theory (DFT) and molecular dynamics (MD) simulations guided the identification of distinct THz “fingerprints” for methanol (~1.2, 1.7 THz) and furfural (~1.4 THz). Calibration experiments demonstrated a strong linear relationship (R2 >0.98) between marker concentration and THz absorption. Compared to traditional methods, the THz approach enables rapid, simultaneous, and non-invasive quantification of multiple indicators, providing a more holistic assessment of insulation health. The results pave the way for field-deployable, online monitoring solutions that support smarter asset management and improved transformer reliability in the context of digital power grids.