The production of Miao women's apparel is the focus of this study's investigation into the inventive applications of artificial intelligence (AI) and machine learning techniques. As a significant development in the sector, we provide an AI-powered strategy that smoothly combines cutting-edge technology with classic components. Customizing body forms, maximizing fabric selection, and creating advanced designs are the three main focuses of our study. We used AI-driven statistical techniques for accurate pattern recognition to adjust to the particular body traits of Miao women. Additionally, AI was utilized to evaluate fabric characteristics to balance comfort and aesthetics while choosing materials. To overcome this limitation, we propose Dynamic Random Frost (DRF) is used for analytical model. The Multimodal Uncontrolled Image-to-Image Translation (MUNIT) technology was used to create chic designs. We are increasing the uniqueness of ethnic clothing. The experimental findings of the proposed method are evaluated by precision (93%), accuracy (91%). This study focuses on the interaction between modern technology and traditional handicrafts, highlighting AI's role in the development of ethnic design that is environmentally conscious. We also stress the significance of Made-to-Measure (MTM) techniques, emphasizing the value of customization in contemporary clothes. This work is a ground-breaking investigation into how AI, pattern recognition, & ethnic fashion design relate to one another, which can potentially alter how the fashion industry functions in the future.