The tourism sector is a labor-intensive sector since it has the characteristics of a service sector, and it has a significant impact on the national economies. The improvement of the sector leads to an increase in production, consumption, and employment within the economy. Tourism is included in the current account of the balance of payments and is an invisible export item. Tourism revenues may allow the high rate of foreign currency inflow in the short-run, and they are vital for countries with current account deficits such as Turkey. In the study, it was aimed to reveal the impacts of tourism revenues on the current account balance over the period 2013-2020 in Turkey, and the relationship between tourism revenues and the current account balance was predicted using the artificial neural network method in line with this purpose. Tourism revenues were used as model (artificial neural network) inputs in predicting the current account balance over the same period, and analyses were performed utilizing the monthly data obtained from the Turkish Statistical Institute (TSI). The obtained findings of the study indicated that 4 different ANN (Artificial Neural Network) models that use lagged variables related to tourism revenues as inputs for the current account balance prediction have a quite successful prediction performance. There was a strong cause-effect relationship between tourism revenues and current account balance.