This chapter presents a systematic framework for developing and validating measurement instruments within the Rasch measurement theory (RMT) paradigm. It emphasizes that effective instrument design requires a clear construct definition, alignment between construct and items, and empirical evidence supporting measurement invariance. The chapter outlines an iterative process that includes defining the construct, developing items, piloting the instrument, analyzing data with Rasch models, and refining items based on empirical results. RMT provides a theoretical measurement model with ideal characteristics that can be combined with diagnostic tools allowing item and test developers to assess item functioning, scale structure, and the degree to which data fit the model-based expectations. Key analyses include examining Wright Maps, category functioning, item fit statistics, and reliability indices. Special attention is given to evaluating unidimensionality, local independence, and appropriate rating scale functioning, as well as detecting differential item functioning across subgroups. Illustrative examples show how Rasch analyses inform decisions about revising or removing misfitting items, adjusting rating scales, and providing validity evidence for score interpretation and use. The chapter stresses that integrating RMT into instrument development can enhance construct validity, measurement precision, and fairness. The resulting measures are better able to support both rigorous research and practical decision-making.