Land grade have a crucial role to play in that it classifies the urban land into differentrnlevel of valuation scales making it possible for urban land valuation. It would enable therndevelopment of appropriate standard benchmark prices on the lease of land and for thernvaluation of land related property. It also brings transparent and clear taxation systemsrnthat could establish sound and efficient land marketing system that would facilitaterninvestment. However, the existing land grade system of the urban centers of Ethiopia likernWeldiya town has not been very successful in allowing the town to benefit from thernadvantages of having an efficient land grading system. The major reasons behind thernlimitations emanates from two main factors. The first reason is related to that paramountrnfactors have not been exhaustively considered in designing urban land grading system.rnThe second problem is related to a methodological approach how land grade is preparedrnand implemented. Moreover, despite the fact that many geographical phenomena likernland grade have fuzzy characteristics, currently most of the geographic phenomena arernrepresented by crisp. Hence, the intent of this study is to develop conceptual fuzzy landrngrade model that is helpful to bring flexible land grading and enables to give decisionrnmakers an informed decision. In any of these methods, factor identification, weightingrnand integrating GIS and fuzzy logic approaches are important prerequisites that serve asrnplatform to develop land grading. To design the conceptual model five main factorsrn(infrastructure, land use, topographic characteristics, visual and environmental factorsrnand population density) have been considered. Twenty four criteria were also consideredrnunder each main factor.The study confirmed that among the identified factorsrninfrastructure takes the lionâ€™s share that has 51% weighting influence and land use is inrnsecond position with weight influence 25.6 %. Topography, environmental and visualrnquality and population density factors have weight influence of 12.6%, 6.9% and 3.9 %rnrespectively. This study used FAHP to determine criteria weights. The fuzzy consistencyrnratio (FCR) result was obtained 0.06. Based on the research findings, the most valuablernland is situated in the old section of the town (CBD) where comprehensive infrastructurernhas been developed. The fuzzy analysis indicated that there is a gradual change in urbanrnland grading pattern. This indicated that flexibility is another characteristic of fuzzy logicrnapplication. The final out put map indicated grade one, grade two, grade three havernpositively increased by 5.37%, 4.28% and 2.85% respectively as compared to the existingrnland grading. This situation is happened due to infrastructure development and expansionrnof the town.rnTo sum up, this paper indicates the fuzzy modeling approach can avoid the loss ofrninformation that often arises when the strict Boolean logic is used on the basis of the crisprnsets (Yes/No) and can produced a better and more reasonable result than crisp. It is alsornconcluded that FAHP is best alternative to determine the criteria weights from judgmentsrnof decision-making domain of experts.