The rapid advancement of Library and Information Science requires thoroughly examining emerging trends and evolving research priorities. This study seeks to uncover key themes within the field by applying Clustering Analysis and Keyword Frequency techniques. The objective is to analyze interdisciplinary connections and shifts in focus areas such as digital libraries, metadata, and information retrieval. Data were collected from 450 librarians through a structured questionnaire and analyzed using SPSS. The findings reveal distinct clusters centered around digital information management, metadata, and open access, while the rising prominence of concepts like data science indicates changing research interests. These insights highlight potential biases in the Library and Information Science literature and suggest opportunities for future research, particularly in areas such as ethical considerations, user-centered design, and scholarly communication. The study's contributions lie in offering a data-driven approach to trend analysis within Library and Information Science, providing practical implications for guiding future research directions and interdisciplinary collaboration. Its novelty stems from integrating computational methods to explore the complex, evolving landscape of Library and Information Science and offer a roadmap for future scholarly exploration.