The aim of the paper is to demonstrate the appropriateness of an a priori analysis to determine the distributional assumption of the inefficiency term in a stochastic frontier model. To this end, theoretical distributions of estimated inefficiency were obtained when the inefficiency term is assumed to be distributed as a half normal and an exponential in a cost frontier model. Comparisons of such theoretical distributions with the respective cost inefficiency estimators using the goodness of fit test allow selecting the most appropriate distributional assumption. The application on three data sets of Spanish banking system in 2009 demonstrated the relevance of the research question. First, the results of estimated cost inefficiency with a half normal assumption are larger than with an exponential distribution significantly. Besides, half normal assumption was rejected and exponential was not rejected as the most appropriate distribution of inefficiency term in Spanish banking data set. However, the adjustment of saving banks data had been better with the former distribution than the latter. In the case of banks, any distribution results appropriate. To sum up, this work demonstrate that the distributional assumption on inefficiency term in Stochastic Frontier Approach must be established in a justified way, as it can significantly bias the results of estimated inefficiency and therefore, influences improving policies and strategies in the Spanish banking sector.