Near infrared (NIR) spectroscopy is especially suitable for online monitoring of the productive process due to its fast and non-destructive detection feature. The online monitoring of cut tobacco is important for cigarette industrial enterprises to guarantee the consistency of product quality. Common practice is to use online NIR spectra and chemical contents of corresponding samples to establish online quantitative prediction models. However, it will be a huge burden to establish and uphold the models in case of multipoint monitoring. Moreover, the difference between instruments and the problem of instrument ageing will confine the working life and range of the established models. The objective of this study was to develop a simple method, which is helpful to conveniently acquire online NIR models for monitoring cut tobacco. A rotating plate was designed to simulate tobacco conveyor, so that standard samples and their spectra in different conditions were obtained for model transferring. Then a chemometric method, Spectral Space Standardization (SST), was successfully utilised to transfer the offline prediction models of tobacco powder into online models of cut tobacco. Hereby, the online monitoring of cut tobacco quality was achieved by examining tobacco components in virtue of the obtained online models. Experimental results of tobacco combustion heat showed that the average prediction relative error (APRE) decreased from 6.5% to 2.7% after model transferring, which was in close proximity to that of the offline model (2.0%). It indicated that SST could eliminate the systematic difference between offline and online spectra of a sample, and the prediction accuracy of online models was almost the same as that of offline models. No more than 20 standard samples are needed for model transfer, so model transfer can be finished in one day, which enables the proposed method to be applied to any section of the tobacco primary processing line or tobacco threshing and redrying line.