The study is a first attempt to quantitatively evaluate an existing satellite-based rain estimation algorithm using a network of ground-based meteorological stations. The study domain is the Epirus Region (Greece), which is one of the rainiest areas of Greece, and where the laboratory of Meteorology and Climatology (Ioannina University) operates eight meteorological stations distributed across the study domain. The utilized version of the rain estimation algorithm is using the Meteosat-11 Brightness Temperature in the 10.8 μm channel (BT_10.8μm) to estimate the rain intensity on a 4 Κm pixel basis, after discriminating the rain/non-rain pixels with a simple thresholding method. The validation procedure consists, at first, in a selection of dates of the year 2019 during which a wide range of rainfall values were recorded. Subsequently, the rain recordings of the meteorological stations’ network were spatiotemporally correlated with the Meteosat-11 data. These correlations finally led to a dataset with 1323 pairs of rain recordings and their relative rain estimations from the satellite-based algorithm. A statistical analysis of these pairs of values was conducted revealing a Mean Error (ME) of 0.22 mm/hr (14% error regarding the mean value of the recordings). Also, basic categorical statistics were calculated to assess the accuracy of the satellite-based algorithm in providing rainfall estimations (in cases that rain recordings from the network of the meteorological stations exist). The computed Probability of False Detection (POFD), Probability of Detection (POD) and the bias score are equal to 0.22, 0.69 and 0.88, respectively. The evaluation statistics are promising with regards to operationally using this algorithm for rain estimation on a real-time basis.