This article proposes a novel algorithm which helps in efficient transmission and storage of medical images. The conventional prediction algorithm is modified in such a way that they provide high compression without any further degradation in the image quality. A binary mask is generated based on the optimized threshold value for the image data. Then prediction is done for the masked coefficients to eliminate high error values caused by lower range of coefficients. An appropriate prediction function which gives less entropy for the input image is selected and encoded. The experimental results showed a maximum of 45% improvement in compression ratio compared to the normal prediction process. The proposed modified prediction algorithm can efficiently replace the prediction step in any lossy or lossless compression algorithms. They can also be utilized as a part of compression in any contextual compression techniques. Any kind of transformation approach can be used in hybridization with this proposed optimized prediction model to perform better.