Natural durability remains one of the most attractive characteristics of wood, and helps wood obtain a premium price. A worldwide shift towards the use of younger trees from intensively managed forests has created greater concerns about wood quality, especially the wood’s resistance to fungi and insects. Wood durability is assessed using a variety of standards. Some standards are based on destructive methods that measure weight loss after exposure to wood degrading organisms. These tests are useful but there are concerns about variabilities in durability classifications according to different testing methods. Furthermore, durability can be heavily influenced by variations within and between trees, sites, regions, genetic origin, and age. Thus, there is a need for a faster, non-destructive and economically viable technique for screening wood durability. Fourier transform infrared spectroscopy with attenuated total reflectance (ATR-FTIR) and near infrared spectroscopy (NIR), with chemometrics analysis was explored for classifying wood durability. The extractive contents of Alaska yellow cedar (Callitropsis nootkatensis) and western juniper (Juniperus occidentalis) were investigated to understand the variability that existed between and within trees, and the relationships between brown-rot decay (Gloeophyllum trabeum and Rhodonia placenta), termite (Reticulitermes flavipes) resistance, and the spectroscopic results were examined. FT-IR showed sensitivity in detecting to one of the extractive concentrations (carvacrol) as differences were observed on 3% concentration. The majority of the Alaska yellow cedar and western juniper samples were classified as resistant to highly resistant against decay fungi and termites. A moderate to poor correlation between extractives and mass loss to wood biodegradations agents (fungi and termites) was observed, indicating the possibility for other factors may contribute to wood superior durability. Chemometrics analysis using principal component analysis (PCA) and hierarchical cluster analysis (HCA) on the spectral data was unable to accurately classify wood based on their durability. Nevertheless, results suggest FT-IR and NIR can be used for analyzing wood extractives, as well as the possibility for producing more accurate predictions on species with greater variability in durability.