Destination image is a critical determinant of tourist behavior, playing a central role in destination choice, satisfaction, and loyalty. While qualitative methods capture emotional and cognitive perceptions, quantitative indicators allow policymakers and tourism organizations to systematically measure, compare, and monitor destination image over time. This study investigates quantitative approaches for measuring destination image, integrating survey-based metrics, digital analytics, media indices, sentiment scores, and visitor behavior statistics. Using mixed-method research involving 600 surveyed tourists, analysis of 8,000 online reviews, and interviews with 20 tourism experts, findings indicate that multi-dimensional quantitative frameworks enable robust evaluation of cognitive, affective, and conative image components. However, challenges include indicator selection, data reliability, cross-cultural variability, and algorithmic biases. A conceptual model and measurement index are proposed to improve destination image assessment