Noun Phrase Recognition, also known as NP chunking, involves identifying and classifying sequences of words that function as noun phrases. Noun Phrase (NP) recognition is a crucial task in Natural Language Processing (NLP),providing foundation for various higherlevel linguistic tasks such as machine translation, information extraction and syntactic parsing. Marathi is morphologically rich and syntactically flexible Indo-Aryan language. While substantial work has been done for English and other resource-rich languages, Indian languages like Marathi pose unique challenges due to rich morphology, free word order and agglutinative features. This paper explores noun phrase recognition in Marathi. This paper presents an algorithm for identifying noun phrases in Marathi language sentences. Based on this algorithm, a computational model has been developed which identifies noun phrases from a given sentence. The rule-based system with the approach of Local Word Grouping has been applied in the process of identifying noun phrases. This task can help in phrase structured based machine translation and thus identifying noun phrases can become the base for other Indian languages. We present an overview of the linguistic structure of noun phrases in Marathi, challenges in automatic recognition, and computational techniques employed. We evaluate both rulebased and machine learning-based approaches.