The hedonic price method is well established as a method for deriving real estate price indices and for identifying the factors that influence real estate prices in the market. Despite a close relationship to the traditional sales comparison approach and conceptual and statistical advantages, the hedonic price method is used much less in the appraisal of individual objects. In recent years, locational facors have been increasingly included into the set of explanatory variables as well as into the specification of the error term. This has not only improved the explanatory power of the method, but also introduced additional challenges for the interpretation of results and particularly for the use of these results for the appraisal of individual objects.The paper discusses the hedonic price approach to real estate appraisal and especially its relation to the traditional sales comparison approach. It will be shown that spatial econometric methods can be applied to improve the power of the hedonic price regression. The main part of the paper will be devoted to the question of how to utilize the results of the hedonic regression for appraisal of individual objects, what challenges the different possible specifications of the regression equation on the one hand and of the structure of the error term on the other hand raise. The paper presents algorithms for handling these computational issues and presents simulation results for each case.