This chapter explores Rasch methodology as a robust approach for developing and validating psychometric measures in international contexts to ensure accurate construct assessment in both research and practice. Unlike Classical Test Theory (CTT), which has been criticized for its reliance on imprecise ordinal data and violation of parametric assumptions, Rasch analysis employs a statistical model that defines precise mathematical links between items and the underlying latent trait. The Rasch model is capable of converting ordinal data into interval-level measures, satisfying the assumptions of parametric statistical techniques and facilitating more accurate and meaningful comparisons across populations. Evidence has demonstrated the growing application of the Rasch model and its advantages for the assessment of psychometric instruments in international research. This is particularly so in the assessment of cross-cultural equivalence by evaluating whether items perform consistently across diverse cultural or linguistic groups. By anchoring items and calibrating person measures on a common metric, Rasch analysis minimizes bias and promotes fair and equitable measurement across different groups. Although Rasch analysis is often associated with item deletion to achieve model fit, we have emphasized that testlet methodology offers a promising alternative for retaining items and thus protecting the construct validity of scales. This chapter serves as a guide for applying the Rasch model across diverse fields to strengthen the scientific rigor of psychometric tools and contribute to the development of more valid, reliable, and equitable assessments that are responsive to individual differences across varied populations. Further research is needed to apply the Rasch Measurement Model to evaluate and enhance psychometric instruments in health-related international contexts.