In order to effectively promote the energy revolution, and promote the rational allocation and optimization of coal resources, making a reasonable evaluation of the coal resources mining rights is the key step. With the development of coal mining rights market, case-based evaluation method will become more and more important in coal mining rights evaluation in the future. But, the existing research has not established a complete coal resources mining rights case valuation method system, especially in case selection and similarity selection. Based on case-based reasoning, and combined with artificial neural network, this thesis set-up a case evaluation model of coal resources mining right. And RBF neural network selection model, case similarity function, weight calculation method are confirmed. Through a practical case of coal mining rights, do researches on the application of this model. The results indicate that the price got from using case-based coal mining rights evaluation method is very close to the final deal price, and that case-based evaluation method is more simple, practical and accurate with the precondition of existence of certain amount of comparable exchange targets.