An important issue in the making of soil surveys is quantifying the value of the information generated and contained in the soil survey. This study uses decision trees, Bayes' Theorem, and map quality evaluation procedures to assess the economic value and economic efficiency of soil surveys. To develop this methodology, a case study is used that considers three different scenarios in which the level of information regarding soil changes. The three scenarios are: (i) site-specific soil information is unavailable, (ii) perfect site-specific soil information is available (not realistic), and (iii) imperfect site-specific soil information is available. The calculated economic value of this hypothetical soil survey was US$ 17.14 ha−1year−1, which is higher than the estimated soil survey cost of US$ 2.09 ha−1. This simple comparison indicates that the soil survey is cost effective and that its costs would be paid off with the gain from the first year of its application. The combination of the calculated economic efficiency (55%) with the physical quality of the map (total percent correct in the map was 80%) allowed a better understanding of the actual value of the soil survey. The use of this method provided a means of calculating analytically a more complex and realistic value of soil surveys.