Nowadays, the emergence of new technologies and the need to use them in the tourism industry has provided the basis for the creation of a new concept called smart tourism. The purpose of this research was to analyze the role of machine learning in smart tourism with the mediating role of electronic customer relationship management. The type of research was applied in terms of purpose and descriptive-correlation in terms of the nature of the method. For sampling, a simple random sampling method was used and to determine the sample size, Cochran's formula was used, and due to the unlimited size of the statistical population, the sample size was determined to be 384 people. Data was collected through three standard questionnaires: "commercial applications of machine learning", "factors affecting the development of tourism in the region" and "electronic customer relationship management". Validity was examined and confirmed by confirmatory factor analysis and reliability using Cronbach's alpha. Data analysis was done with structural equation modeling method and with the help of SPSS 26 and Smart-PLS 3 statistical software. Based on the research findings, machine learning has a positive and significant effect on smart tourism and electronic customer relationship management, as well as electronic customer relationship management on smart tourism. In addition, electronic customer relationship management plays a mediating role in the relationship between machine learning and smart tourism. The findings of this research can be effective in the movement of tourism companies towards the application of machine learning and the implementation of electronic customer relationship management.