The identification of tumors is one of the most tenacious and emerging fields in medical image processing. A tumor means the unrestricted existence of a bunch of cells in a precise area of the human body which destroys the normal body cells and keeps increasing. In human body, brain tumor is measured as the most common tumor which affects the nervous system, memory functional cells, glands, and membranes that surround the brain and can conduct to a high mortality rate if the affected one is unsuccessful to reach proper medical treatment. For effective treatment, precise and early recognition of the tumors is critical work and also a vital step in diagnosis and treatment preparation for affected one which not only benefits to arise with improved medications but also saves the affected life in due time. This research work uses Magnetic Resonance Imaging (MRI), which is a prominent imaging procedure in terms of brain tumor recognition. For features extraction, segmentation and classification, the proposed research work includes the deep neural network integrated method and Convolutional Neural Network (CNN) to classify the MRI images and an accuracy of about 97.92% has been achieved.