This paper evaluates nine alternative accrual-based models for detecting earnings management. The Evaluation compares the two type errors (type I and II). The empirical analysis is conducted by testing for earnings management using three distinct samples of firm-years:A) Randomly selected sample of 1000 firm-years,B) Sample of 1000 randomly selected firm-years in which a fixed and known amount of accruals manipulation has been artificially introduced; and c) A sample of firms that we have strong evidence to that their earnings have been managed. Sample (A) was designed to investigate the type I error. Type I error arise when the null hypothesis, that earnings are not systematically managed, is rejected when the null is true. Samples (B) and(C) were designed to test the type II error. Type II error arises when the null hypothesis, that earnings are not systematically managed, is not rejected when it is false. In this paper, Type II error is generated in two ways. First, we use simulations in which earnings have been artificially manipulated by added a fixed and known amount of accruals. Second, we use another set of firm-years, for which we have strong priors that earnings have been managed. The empirical analysis generates the following major evidences. First, all of nine models appear well when applied to investigation the type I error. Second, regression-based models (Jones1991, Modified Jones 1995, Dechow et al 2002, and Two deflated models) to detect earnings management, introduces the lower type II error than naïve models(Healy1985, De Angelo 1986, Modified De Anglo 1994). Third, the modified Jones model 1995, and Dechow et al 2002, have lower type II error than the other regression-based models.