The brain tumor is situated in the brain of patient they might extremely threaten their life. The influence and outcome of the factor of brain tumor to improve treatment and controlled the disease. For identification of brain tumors, various studies have been carried out. In addition, laborious with respect to execution time and laboratory equipment some of them were expensive though others have not expressed the desired results. A research study we are used segmentation and classification through intelligent computational model for brain tumor. This schema of study using 2013 BRATS dataset four modalities of MRI. The required range and pre-processing image applied the different techniques for the achievement of numerical attributes for segment area like enhancing tumor, complete tumor and core tumor. The total number of 58 feature are removed. Now the random forest (RF) use for the training and testing for feature array. The proposed model used the 10 cross validation method to enhance the performance of model. The proposed model shows the better results as compare to the other machine learning. 

Keywords: Brain tumor segmentation, feature extraction, Resent classifier.