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Model-oriented methods to predict antenna noise temperature due to rainfall along slant paths are developed and illustrated for communication systems at Ka-band and above. The adopted Sky Noise Eddington Model (SNEM) relies on an accurate analytical solution of the radiative transfer equation and on stratiform and convective rainfall stratified structures, synthetically generated from cloud-resolving model statistics. The approach to predict antenna noise temperature is based on the multiple regression analysis, trained by SNEM-derived cloud radiative data sets, and can handle either slant-path attenuation or columnar liquid water or rain rate as input predictors. Statistical scaling with respect to frequency and zenith angle is also analyzed and modeled in the microwave and millimeter-wave range. In order to test the proposed prediction technique, measurements of the ITALSAT satellite ground-station at Pomezia (Rome, Italy) are taken into consideration for two case studies. Combined data from the ITALSAT three-beacon receiver at 18.7, 39.6, and 49.5 GHz and from a three-channel microwave radiometer at 13.0, 23.8, and 31.6 GHz are processed. Results are shown and discussed in terms of antenna noise temperature estimation by using the satellite-beacon path attenuation as predicting variable.