This paper presents the discrepancies in applying the power-law model (PLM) for predicting indoor airflow distribution and the methodologies employed to improve this model. First, investigation was made to find an appropriate K value (flow coefficient) for use within the PLM (using the same K value for each cell). Values other than 0.83 were considered, and the result revealed that values other than K = 0.83 could not affect the prediction of the PLM and that K can be given any value, such as 1.0. The result also showed that the PLM could not be improved by using the same K value for each cell. Therefore, to improve the prediction capability of the PLM, other methodologies were pursued: (1) estimating the K value for each cell and (2) combining the PLM with another zonal model—the surface-drag flow model (SDM). The first approach has made the PLM to have variable K values and is referred to herein as PLMK. In the second approach, two types of combination were explored: direct and indirect. The direct combination of the SDM and the PLM has provided different forms of zonal models such as SD-PLM1, SD-PLM2, and SDPLM3, and the indirect combination gave the modified powerlaw model (MPLM). Comparison of the predictions of all these models with each other and with experimental data showed that the MPLM provides the best predictions of the recirculation in the standard zone, followed by the PLMK.