A sample is a subset of individuals, households, organizations, or units selected from a larger population for the purpose of conducting research. Instead of collecting data from every member of the population, researchers gather information from a carefully chosen sample and use the findings to make inferences about the entire population. In research methodologies, especially in Gender and Development Studies, sampling is an essential process because it enables researchers to examine gender-related issues such as inequality, access to education, employment, health, political participation, and social empowerment in a practical and systematic manner. A good sample should be representative of the population so that the results accurately reflect the characteristics, experiences, and perspectives of different gender groups, including women, men, and gender minorities. Sampling can be conducted using probability methods, such as simple random sampling, systematic sampling, stratified sampling, and cluster sampling, where every unit has a known chance of selection. It can also be carried out using non-probability methods, such as purposive, quota, convenience, and snowball sampling, which are particularly useful when studying marginalized or hard-to-reach populations. In Gender and Development Studies, purposive and snowball sampling are often employed to reach survivors of gender-based violence, transgender communities, migrant women workers, or other vulnerable groups. Sampling offers several advantages. One of its major merits is that it saves time because researchers collect information from only a selected portion of the population rather than every individual. This is especially valuable in large-scale gender studies involving geographically dispersed populations. It also reduces the cost of research by minimizing expenditure on travel, data collection, personnel, and data processing. Another important merit is that sampling makes research more manageable. Researchers can focus on