This study presents a short-term prediction approach for honey production using ensemble regression technique. The data were recorded as a part of Habeetat project in Sarajevo, Bosnia and Herzegovina for 2016 season. This season has been entitled as one of the worst seasons for beekeepers in our country, which makes the problem of honey production prediction even more challenging. Random Tree regression algorithm was used for such purpose showing that the mean absolute error in predicting total honey production was less than 1.16 kg in all three hives monitored between November 2016 and April 2017. These findings are very significant for beekeepers since they can be notified in advance to visit individual hives and collect the honey. Besides, they can monitor trends in honey production throughout the season and perhaps change the position of hives in the current season and for the next upcoming season.