Online news portal and other media on the internet now produce the large amount of text, which is mostly unstructured in nature. When an individual wants to access or share particular news, it should be organized or classified in the proper class. Nepali news classification is the task of categorizing the news content into the predefined category from the training news dataset. In this project, a system has been built for categorizing the content of the news into different categories using the news article from a major Nepali language newspaper published in Nepal. This project evaluates some widely used machine learning techniques mainly Naïve Bayes for automatic Nepali News classification problem. It classifies the news by analyzing the content of the news. In the system, a self-created Nepali News Corpus with 16 different categories and total 16719 documents collected by crawling different online national news portal is used. The test showed the accuracy of 83.94% in the news classification using Naïve Bayes. In the system, the user can categorize the news based on their content by analyzing the news content from various Nepali language newspaper and clicking the categorize button.