We propose an alternative methodology to identify episodes of credit boom based on economic fundamentals. A credit boom is defined as a period during which the level of credit deviates “excessively"" from its trend after registering a period of persistent growth. The proposed methodology models credit deviations as a function of: (i) economic fundamentals, and (ii) a state variable that is not observable, which measures the component of credit deviations that is not associated with fundamentals. A credit equation is then estimated from its state-space representation (SS) using the Kalman filter (FK). The proposed methodology is applied to the case of Peru using monthly data for the period January 1994-September 2012. The results suggest two possible episodes of credit boom in Peru, whose peaks were reached in November 2008 and May 2011, respectively.