In the framework of the activities of the IAG sub-commission on gravity and geoid in Africa, it is needed to have a uniform gridded gravity data set to determine the earth's mathematical surface (the geoid) in Africa using Stokes' integral in either the frequency or space domain. The available gravity data set for Africa consists of land point gravity data as well as shipborne and altimetry-derived gravity anomaly data. The available gravity data set has significantly large gaps, while in some particular areas the distribution is fairly dense. Also the shipborne and altimetry data have a line structure (along tracks). This leads to a problem in determining a reasonable empirical covariance function, and consequently limits the capability of the used least-squares prediction technique. Filtering the available gravity data and degrading the ocean gravity data took place to overcome this problem. The establishment of the updated gravity database for Africa has been carried-out using the well-known RTM reduction technique, employing a weighted least-squares prediction technique. The land gravity data get the highest precision, while the shipborne and altimetry gravity data get a moderate precision. The data gaps are filled with gravity anomalies derived from the GOCE_DIR_R5 global reference model, getting the lowest precision within the prediction technique. The weighted least-squares prediction technique is thus carried-out to estimate gridded gravity anomalies. The updated gravity database AFRGDB_V2.3 has been established after performing the proper RTM restore step. The precision of the developed gravity database is tested on internal and external levels.