This paper presents an appraisal model of real estate in Thailand using fuzzy logic which is a method for a capable of solving any value in blank land submarkets relative to clustering methods based on classic (or crisp) set theory. The valuer shall record the inspection result regarding condition and location of such land. Systematic analysis shall be applied and the fact of the land's condition will also be recorded. Generally, such valuation data will be taken to compare with other comparable data and then classified by the valuer according to its significance, namely, A, B, C and D. This classification criteria is still not clear, especially weightedfactor of such property (Effective Factor of Property). Therefore, this problem has drawn attention from the researcher to explore the causes of such problem and at the same time propose models for clustering using fuzzy as a tool for classifying thecomponents of the property (Effective Factor of Property) in order to determine upon such vagueness regarding weightedfactor.Issues of choosing algorithm parameters are discussed on the basis of applying fuzzy clustering to 101 metropolitan areas in the Thailand. The result from the experiment shows that the components of the property are weighed more appropriately and closely to the real value which can give the percentage of reliance to be at approximately 97 %. This enables the valuer to determineand make a comment on property value that its evaluated value becomes closer to the real one to the greatest extent.