Objective: The objective of this study was to develop the Menstrual Migraine Symptoms Scale (MMSS). Methods: The study utilized a robust methodological design with a sample size of 582 participants. The data underwent a comprehensive analysis employing various statistical techniques, including item analysis, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Cronbach’s alpha internal consistency coefficient, and the Intraclass Correlation Coefficient (ICC) for test-retest reliability. To collect the study data, Google Forms was employed for both the Socio-Demographic Characteristics Form and the MMSS. Results: The two sub-dimensions of the scale, consisting of 19 items, demonstrated excellent internal consistency, with Cronbach’s alpha coefficients ranging from 0.932 to 0.970. Furthermore, the total scale exhibited a high level of internal consistency, with a Cronbach’s alpha coefficient of 0.976. The item correlation values within the scale ranged from 0.741 to 0.921, indicating strong relationships between the items. Following the identification of the factor structure through EFA, the construct validity of the scale was further assessed using CFA with an additional dataset. The results of the CFA demonstrated that the scale performed exceptionally well across all evaluation metrics, affirming its reliability and validity as a measurement tool with a robust two-factor structure. Conclusion: The study findings conclusively demonstrated the validity and reliability of the MMSS as a robust measurement tool specifically designed for assessing female individuals. With its proven accuracy and consistency, the scale can be confidently employed to reliably evaluate and monitor menstrual migraine symptoms in women.