The paper examines Machine Translation Systems for various Indian languages, including Dogri language. Our research mainly focuses on English-Dogri language machine translation. Dogri is considered a low-resource language. Statistical Machine Translation (SMT) tools such as Moses gained lots of popularity, but now deep learning technologies have significantly changed the field. This paper focuses on comparing the standard SMT systems with the cutting-edge Neural Machine Translation (NMT) models for translation of English to Indic languages with special reference to English-Dogri language pair. This work also proposes a research methodology for constructing a Machine Translation System from English to Dogri utilizing a deep learning approach. © 2025 IEEE.