Near infrared spectroscopy is a non-invasive and rapid technique to support the analysis of solid biofuels such as woodchip, which is considered as a suitable alternative for energy production, according to European goals for fossil fuel reduction. Chemical and physical properties of the woodchip influence combustion performance, so the most discriminant parameters such as moisture and ash content and gross calorific value were constantly monitored. The aim of this study was the development of prediction models for these three parameters with the use of a hand-held NIR spectrometer. Laboratory analyses were carried out to evaluate the quality of several Italian samples from a power plant, and PLS regression models were developed to test prediction accuracy. Moreover, the most relevant wavelengths were investigated to discriminate chemical compounds influence. Prediction models demonstrated the capacity of handheld MicroNIR instrument to be considered a practical tool for solid biofuel quality assessment. As a consequence, NIR spectroscopy improved real-time analysis and made it suitable for practical and industrial applications, as supported by the recent Italian standard UNI/TS 11765.