A crucial aspect of medical diagnosis is the classification of brain tumors. Identification of tumor type is very much needed for the correct and effective treatment. In this research work a deep learning approach for the classification of brain tumor based on MRI images using Convolutional Neural Networks (CNNs) is introduced. The CNN model developed in this research work extract features from the preprocessed brain MRI images and categorize them based on the tumor identified. The CNN model was also compared against the conventional machine learning classification models such as such as Recurrent Neural Network (RNN), K-Nearest Neighbor (KNN), Random Forest, Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and Artificial Neural Network (ANN) based on the experiments performed. The outcome shows that the CNN model outperformed the other algorithms by achieving the accuracy of 96.98%. This book chapter highlights the potential of CNNs to classify the brain tumor accurately and provide support in diagnosis decisions.