We propose an extension of the existing information criterion‐based structural break identification approaches. The extended approach helps identify both pure structural change (break) and partial structural change (break). A pure structural change refers to the case when breaks occur simultaneously in all parameters of regression equation, whereas a partial structural change happens when breaks occur in some parameters only. Our approach consistently outperforms other well‐known approaches. We also extend the simulation studies of Bai and Perron ( and Hall, Osborn and Sakkas () by including more general cases. This provides more comprehensive results and reveals the cases where the existing identification approaches lose power, which should be kept in mind when applying them.