This paper proposes a direct data interpolation method for predicting ferrite core loss in power electronics. The core idea is to accurately construct the B-H loop shape given arbitrary Hfield waveforms. Unlike conventional loss models like the Steinmetz equation and its variations, or recent neural network methods like MagNet that leverage periodic B-H waveforms and frequencies, this method employs a data segmentation and reconstruction process to fully exploit the distinctive features of the B-H loop under varying conditions. The source data is from Princeton University's MagNet open-source datasets.