Accounting choices have significant impacts on companies’ accounting results which are closely monitored by managers, investors and government agencies. This paper proposes an intelligent system based approach to accounting choices evaluation and selection. The approach addresses the accounting choice decision making problem from a novel perspective. To select the most suitable accounting choice method, an artificial neural network model is developed to examine the complex interactions between operational data and accounting results. By applying intelligent and multicriteria decision making techniques, this paper takes a broader scope that is traditionally challenging in predicting and evaluating the consequence of alternative accounting methods with regard to business strategic goals. Results of a preliminary study provide new insights into accounting choice selection problems. This paper contributes to accounting choice research by proposing a new approach for filling existing gaps and providing solutions for accounting choice decision making in practical settings.