In this project, I used dataset which had been collected from Azerbaijani news portals. The dataset consists of 50000 news having 6 distinct categories. Using the Natural Language Processing (NLP) methods, I firstly represented the texts as numerical data and then developed and optimized models to classify the category of news in Azerbaijani language. In the first part of the project, I used Bag of Words (BoW) method to vectorize the dataset and then used several Machine Learning algorithm to train different classification models. As this dataset is labeled, I trained Supervised ML algorithms, namely, Decision Tree Classifier, Naive Bayes, Support Vector Classifier (SVC), and Artificial Neural Network. For the comparison purpose of this project, I used another NLP technique which was Term Frequency and Inverse Document Frequency (TF-IDF) to vectorize data and did the same modeling tasks.