Handloom industry within Garhwal region of Uttarakhand forms a vital segment of traditional Indian textile sector while supporting many workers particularly those from Bhotia community living near border mountain areas. The research presents a machine learning structure to boost productivity while sustaining sustainability and cultural heritage in handloom industry operations. The research project links statistical analysis methods to conventional handloom techniques while studying how Bhotia artists apply art forms when making their handcrafted textiles. The study examines the heritage value along with the cultural meaning of these arts to discover economic growth prospects while protecting cultural heritage among local communities. Using sophisticated machine learning methods the paper examines both current governmental policies as well as sector-specific challenges and opportunities for including technological advancements. The paper utilizes quantitative research methods to demonstrate essential findings using tables and statistical models which propose technological methods and data-based solutions to revitalize the handloom industry without compromising its cultural heritage. The study provides significant insights about utilizing machine learning tools to boost productivity levels while upholding business ethics and enhancing performing art and visual art functions in this conventional sector.