This document presents a method for automatic language identification that uses a hybrid approach combining n-gram text processing and Naive Bayesian classification algorithms. The method first preprocesses text documents by removing special characters, suffixes, and generating tokens. It then extracts n-gram features from the text and calculates n-gram frequencies. Finally, it uses the n-gram frequencies as inputs to a Naive Bayesian classifier to identify the language of the document. The approach is able to identify languages like Hindi, English, Gujarati, and Sanskrit without requiring any prior information about the number of languages or initial partitioning of texts.