Random sampling remains a cornerstone of modern research, ensuring representativeness and minimizing bias in data collection. As research methodologies evolve alongside technological advancements, the relevance of random sampling techniques continues to expand across disciplines. This study examines the role, application, and significance of random sampling in contemporary research contexts, emphasizing its contribution to validity and generalizability. This study employed a literature review research design, synthesizing scholarly articles, methodological papers, and empirical studies published within the last decade. Sources were systematically selected based on relevance to random sampling applications in quantitative, mixed-methods, and large-scale data-driven research. The review focused on identifying common practices, strengths, limitations, and emerging trends associated with random sampling techniques. Findings indicate that random sampling is widely utilized in modern research due to its ability to produce unbiased estimates and enhance external validity. Variants such as simple random sampling, stratified sampling, and cluster sampling were frequently applied across diverse fields, including healthcare, education, and social sciences. The integration of digital tools and statistical software has improved the efficiency and accuracy of sampling processes. However, challenges such as accessibility of sampling frames, cost constraints, and potential non-response bias persist. The study underscores that random sampling remains indispensable in ensuring methodological rigor. Its continued relevance is reinforced by advancements in technology that facilitate large-scale and complex data collection. Researchers are encouraged to combine random sampling with innovative strategies to address practical limitations, thereby strengthening the credibility and applicability of research findings in modern scientific inquiry.