Nowadays, most attention is focused on physical and non-destructive methods, such as NIRS, to measure the chemical composition of rangeland species. Therefore, the purpose of this study is to provide calibration models for Infrared NIRS to estimate the forage quality of shrub species, so that in addition to saving time and cost, the quality of these plants could be estimated with proper accuracy. For this purpose, 654 samples of vegetative, flowering and seeding stages were irradiated by the DA7200 Perten Instrument to estimate the values of nitrogen (N), crude protein (CP), acid detergent fiber (ADF), dry matter digestiblility (DMD) and metabolizable energy (ME) via NIRS. Then, the data were transferred to the Unscrambler software for multivariate analysis. Before fitting the model, S.Golay and SNV methods were used for normalization of data distribution. Calibration and validation of model were performed using PLS1 method and Cross Validation method, respectively. Then, the predictability of models was evaluated by considering the calibration statistics. A total of 18 calibration programs were developed. Considering the calibration statistics, it could be said that the coefficient of determination was above 80% in all the factors studied. Also, at all growth stages, the correlation coefficient between the reference data and the data estimated by NIR was above 90%. Our results clearly showed that NIR calibrations obtained in this study could be used in current and future programs to assess the forage quality of shrub species used by livestock.