Objectives: When it comes to migration, the migration of young people comes to mind and the migration of the older adults is ignored. While, migration after retirement is an important and increasing phenomenon. The reasonsand destinations of migration of the older persons are different from those of the young. Young people usually migrate to urban destinations and further distances with more job opportunities, while the elderly choose closer destinations and rural areas with good climate. This essay study internal elderly migration, patterns and differences between various socio –demographic groups in Iran during period of 2011-2016. Method: This article examines the migration of older adults and its socio-demographic correlates in the period of 2011-2016 using the secondary analysis of the 2016 micro-census data. The sample includes 140,159 aged 55 and over in 31 provinces of the country, both urban and rural areas. Binary logistic regression was used in SPSS26 software for data analysis. Results: The results of multivariable analysis showed that elderly men 13 percent are more likely to migrate than elderly women. The relationship between age and migration for elderly menwas U-shaped, which means that the probability of migration is high at the age immediately after retirement, then gradually decreases with age and finally increases again at the age of over 85 years. Also, the possibility of migration among the unmarried older adults is 36 percent higher than married older adults. In addition, with the increase in the level of education, the possibility of migration of the elderly increases.The probability of migration of the elderly with university education was 2.3 times that of uneducated elderly. Conclusion:Based on the results of census 2011-2015 in Iran, it is expected that the migration of the elderly will increase in the future with the increase in the education level of the elderly and changes in living arrangements. Therefore, it is important to pay attention to the migration of the older adults and its drivers in social policy making.