River’s slope (bed and flow) is a key parameter in fluvial hydrology, hydraulics and geomorphology. It affects many important fluvial variables such as flow velocity and sediment transport, especially bedload. Limitation in river’s slope data confined fluvial modeling, particularly at large scales. Traditional slope calculation algorithms cannot accurately predict river’s slopes as these are based on cell-by-cell calculation, which is only suitable for hillslopes and steep mountainous streams. This paper presents a new algorithm for calculating global river’s slope and a procedure to upscale it for relatively course resolution global hydrological modeling. The algorithm is based on a simple principle of calculating slope from elevation depression over the length of a river segment. The algorithm automates this calculation for global rivers. In this paper, the HydroSHEDS 15 arc-sec Digital Elevation Model is used for calculating global river network and retrieving the elevation values. A sensitivity analysis is conducted in order to examine the effect of maximum river segment length on slope predictions. An analysis of the accuracy of this dataset has been conducted by comparing the new dataset against observed slope data collected from the literature and an independent high-resolution stream network layer for the contiguous United States. The results show that this algorithm is able to accurately calculate global river’s slope. Applications of the resulting dataset are proposed.