Data from approximately 10,500 wells and more than 700 ground level data sets were used to develop a three-dimensional (3D) estimate of the subsurface temperature distribution in Germany. The temperature model was realized with universal kriging, and extends from ground level to 5000m below sea level. Conventional two-dimensional (20) mapping algorithms are often used to estimate subsurface temperature at certain depths. The major limitation of any 2D mapping is the possibility of inconsistencies between different depths due to the loss of information from shallower levels. A different approach is used in this paper. The application of 3D-kriging in the context of subsurface temperature estimation is described in detail and variation of data density and quality are also discussed. Kriging employs customized prediction parameters for an unbiased estimate of the subsurface temperature distribution. The kriging variance predicts the uncertainty of the temperature estimate and provides a local probability interval of the temperature estimate. The developed temperature model is part of the Geothermal Information System for Germany (GeotIS). (C) 2012 Elsevier Ltd. All rights reserved.