This paper describes the research and development of a neural network, Farm Appraiser, that could conceivably reduce the amount of time required for an agricultural appraisal and could also significantly reduce the cost. Neural networkshave been successfully applied to urban residential appraisal. However, very little if any application of this technique has been applied to the agricultural market. For this research, Farm Appraiser was trained and tested with 155 real farmland sales data in Mason County, Illinois. The current neural network predicted the price of farmland averaging 90% of actual selling price which is quite impressive prediction for this type of application. Given the speed of the appraisal (matter of seconds) and ease of use, this system could significantly expedite the appraisal process and considerably reduce the cost.