Cancer is a genetic and vital disease. In last decade, many important genes responsible for the genesis of various cancers have been discovered, their mutations precisely identified, and the pathways through which they act are been characterized. Mammography is the most common technique used by radiologists in the screening and diagnosis of the cancer cells. This project work presents an extension in computer-aided diagnosis for early prediction of cancer cells in brain using Texture features and neuro classification logic. The project extracts the texture from the given brain MRI sample using discrete wavelet transform and morphological operation followed by neuro classification for prediction of Cancer for a given sample. The task works on the extraction of five distinct features with calculation of minimum distance for the prediction of brain cancer. This project work is to be implemented on matlab environment with biological toolbox support for the implementation and verification of proposed system.