Aboveground Net Primary Production (ANPP), an indicator of ecosystems' ability to capture and convert solar energy, is critical to evaluate and manage ecosystem carbon balance index including rangelands. Measuring ANPP over a large area is difficult at it varies with different factors including climate and anthropogenic, while satellite-based information shows strong opportunity. The aim of this study was to estimate the ANPP of Plant Functional Types (PFTs) using Landsat-8 imagery over the rangelands of Hir-Neur from Ardabil Province, Iran as a case study area. Landsat-8 Operational Land Imager (OLI) satellite images were collected on 9^th June 2017 aligning with the field sampling of PFTs ANPP. Eleven sampling sites with 10 plots at each site (locations recorded with a Global Positioning System, GPS) were selected along a transect with elevation gradient and the ANPP of PFTs were recorded. Twenty-two vegetation indices were calculated from the Landsat-8 imagery and the index values were extracted for the sampling plots. Correlation between derived indices and field collected ANPP data were calculated. Predictive relationships between PFTs and total ANPP and satellite indices were developed using a 3^rd-order polynomial model and the model was used to map the whole study area. The best estimation of PFTs and total ANPP was obtained using the Vegetation Index (VI3) for grasses (R²=0.47), Iron Oxide (IO) for forbs (R²=0.51), and Renormalized Difference Vegetation Index (RDVI) for shrubs (R²=0.50). The Difference Vegetation Index (DVI) was the best estimator for the total ANPP (R²=0.49). The overall accuracies of the maps were acceptable (MAE, MDE, RMSE <0.5). Results showed a difference when using PFTs for ANPP estimation in comparison with direct ANPP estimation. Thus, direct estimation of ANPP from the satellite based indices would be more accurate. This study also showed promising capabilities of the indices based on PFTs and total ANPP for estimating aboveground biomass, supply-demand balance and carbon balance at the study area and elsewhere with similar ecological conditions. This study also showed opportunity to select the most appropriate vegetation indices for the estimation of PFTs and the total ANPP.