Rain attenuation poses a significant challenge for high-throughput communication systems. In response, this paper introduces an artificial intelligence (AI) model designed for predicting and mitigating rain-induced impairments in high-throughput satellite (HTS) to land channels. The model is based on three AI algorithms developed using 3D antenna design to characterize, analyze, and mitigate raininduced attenuation, optimizing channel quality specifically in the United Arab Emirates (UAE). The study evaluates various parameters, including rain-specific attenuation, effective slant path through rain, raininduced attenuation, signal carrier-to-noise ratio, and symbol error rate, for five conventional modulation schemes: Quadrature Phase-Shift Keying (QPSK), 8-Phase Shift Keying (8-PSK), 16-Quadrature Amplitude Modulation (16-QAM), 32-QAM, and 64-QAM. Additionally, the paper introduces a new database detailing rain-induced attenuation in HTS channels in the UAE at different frequencies using measured rainfall intensities. The paper concludes by proposing a smart antenna design with a frequency diversity technique for fade mitigation. Results indicate that rain-induced attenuation varies significantly based on rainfall rate and frequency. Specifically, at 25 GHz and a rainfall rate of 100 mm/h, the rain-induced attenuation can reach as high as 15 dB, resulting in a significant decline in signal quality and link performance. The The associate editor coordinating the review of this manuscript and approving it for publication was Ravi Kumar Gangwar .