In recent years, the intersection of fashion and technology has given rise to a transformative design paradigm algorithmic fashion design. Unlike traditional design approaches driven by artistic intuition and manual iteration, this emerging methodology utilizes data, algorithms, and computational tools to create fashion that is both personalized and scalable. From AI-powered trend analysis to generative design software, algorithmic processes are redefining aesthetics, production, and consumer engagement within the industry. This paper explores the conceptual foundation and practical evolution of algorithmic fashion design, analyzing its impact on creativity, efficiency, and sustainability. Through a multidisciplinary lens, the study investigates how machine learning, parametric modeling, and big data analytics enable designers to craft garments that reflect individual preferences while meeting industrial demands. Additionally, the ethical and cultural implications of this technological shift are considered, especially concerning authorship, authenticity, and inclusivity. The findings highlight not only the immense potential of data-driven personalization in revolutionizing the fashion landscape but also the challenges it introduces. As the industry moves toward Industry 5.0, algorithmic fashion design stands as a vital bridge between human expression and computational intelligence, ushering in a new era of smart aesthetics and responsible innovation.