Low-latency communication is one of the most important application scenarios in next-generation wireless networks. Often in communication-theoretic studies latency is defined as the time required for the transmission of a packet over a channel. However, with very stringent latency requirements and complexity constrained receivers, the time required for the decoding of the packet cannot be ignored and must be included in the total latency analysis through accurate modeling. In this paper, we first present a way to calculate decoding time using \textit{per bit} complexity metric and introduce an empirical model that accurately describes the trade-off between the decoding complexity versus the performance of state-of-the-art codes. By considering various communication parameters, we show that including the decoding time in latency analyses has a significant effect on the optimum selection of parameters.