Grain size and beach slope are critical factors in coastal science and management. However, it is difficult to have information on their distribution everywhere in the world, as most of the coast has never been documented. For many applications, it is essential to have at least a rough estimate when local field measurements are not available. Here, we review the existing prediction formulas relating beach slope to grain size and wave conditions, using publicly available global datasets and comparing them with a benchmark dataset of ground measurements from different authors worldwide. Uncertainties arise from the input parameters, in particular coastal waves, a key parameter of all formulae, but also from empirical coefficients that are undocumented or inaccessible with the global dataset. Despite the recognized importance of tides, they are often overlooked in formulae relating beach slope to sediment grain size. We therefore present an improved formulation that incorporates tidal effects. Although satellites offer a promising alternative to predictive formulae for direct estimation of beach slope and grain size, the current accuracy and methodologies of satellite data are insufficient for global applications. Continued advances in satellite missions, including higher resolution and revisit frequency, as well as new sensors, are essential to improve predictive capabilities and facilitate wider implementation.