A crucial safety concern for UHF MRI is the significant RF power deposition in the body in the form of local specific absorption rate (SAR) hotspots,leading to dangerous tissue heating/damage. This work is a proof-of-concept demonstration of an artificial intelligence (AI) based real-time MRI safetyprediction software (MRSaiFE) facilitating safe generation of 3T and 7T images by means of accurate local SAR-monitoring at sub-W/kg levels. Thisfeasibility study demonstrates that SAR patterns can be predicted with a root-mean-square error (RMSE) of <11% along with a structural similarity (SSIM)level of >84% for both field strengths.