Stopping criteria for the iterative decoding of low- density parity-check codes are considered. For a successful deco- ding task an inherent stopping criterion is used: the fulfillment of all parity-check constraints. For an unsuccessful task the decoder usually completes a preset maximum number of iterations. Proper iteration control is required to save energy and time on unnecessary decoder operation when processing undecodable blocks. In this paper we propose an iteration control policy that is driven by the combination of two decision metrics. One is the number of satisfied parity-check constraints and the second one is provided by a specific message computation kernel: the Self- Corrected Min-Sum decoding algorithm. Our results show that this hybrid control policy offers superior performance in terms of energy efficiency compared to previously proposed techniques. In addition we show empirically how stopping criteria should be tuned as a function of false alarm and missed detection rates.