Model transformations play a cornerstone role in Model-Driven Engineering as they provide the essential mechanisms for manipulating and transforming models. The use of assertions for checking their correctness has been proposed in several works. However, it is still challenging and error prone to locate the faulty rules, and the situation gets more critical as the size and complexity of model transformations grow, where manual debugging is no longer possible. Spectrum-Based Fault Localization (SBFL) is a technique for software debugging that uses the results of test cases and their corresponding code coverage information to estimate the likelihood of each program component (e.g., statements) of being faulty. This paper describes a proposal for applying SBFL for locating the faulty rules in ATL model transformations. The approach aims at automatically detecting the transformation rule that makes an assertion fail.