Tumor are a group of tissue that develops abnormally as cells divide and multiply more rapidly than normal cells. In the UK, an average of 429 kids under the age of 14 and 563 kids and teenagers under the age of 19 receive a glioma diagnosis each year. The two types of tumors are malignant and benign, respectively. Glioblastoma Multiforme (GBM) is a devastating brain cancer that can result in death in six months or less, if untreated; hence, it is imperative to seek expert neuro-oncological and neurosurgical care immediately, as this can impact overall survival. Glioma are most frequently discovered via Magnetic Resonance Imaging (MRI) scans. In this work Bayesian modelling is used to identify the glioma. Bayesian algorithm gives efficient output and the work is validated by the performance metrics (Precision, accuracy, Mathew’s correlation coefficient (MCC), Dice coefficient, Kappa). By using these algorithms on MRI scans, brain cancers can be found more rapidly and accurately. The previous work gives an overall accuracy rate of 90% with 75% detection rate of glioma image and 60% detection rate of no tumor images.