This study explores the possibility of developing an artificial neural networks model that could be used to predict monthly average daily total solar irradiation on a horizontal surface for locations in Uganda based on geographical and meteorological data: latitude, longitude, altitude, sunshine duration, relative humidity and maximum temperature. Results have shown good agreement between the predicted and measured values of total solar irradiation. A correlation coefficient of 0.997 was obtained with mean bias error of 0.018 MJ/m(2) and root mean square error of 0.131 MJ/m(2). Overall, the artificial neural networks model predicted with an accuracy of 0.1% of the mean absolute percentage error. (c) 2008 Elsevier Ltd. All rights reserved.