Fourier transform infrared (FTIR) spectroscopy is a well-known method of analysis, with various applications, including promising potential for analyzing biological samples. In the bio-spectroscopy of cells, Mie scattering may increase, which then causes spectral distortion, due to the similarity of cell size with the IR medium-wavelength. These changes make the spectrum unreliable. In previous scattering elimination studies, questionable estimations were considered. For instance, all cells were considered as spherical objects or cell size was estimated randomly. In an attempt to provide the best equation based on the natural existence of cells for the FTIR Mie scattering correction, we examined the actual biological data of cells - as opposed to those yielded from mathematical manipulations. So five biological factors: cell size, shape, granularity, circularity, and edge irregularities, for each cell line were considered as factors which cause scattering. For measuring cell size, roundness and edge irregularity, microscopy images were obtained and processed. For evaluating cell line granularity, flow cytometry was used. Finally, by including these factors, an algorithm was designed. To assess the accuracy of the proposed algorithm, the trypsinized cell spectrum was considered as the high scattering spectrum. Cells were also cultured on a MirrIR slide, and their ATR-FTIR spectrum was considered as the minimum scattering spectrum. The algorithm using the abovementioned five characteristics was used for 13 different cell lines, and in some cases the corrected spectrum demonstrated more than 97% resemblance with the ATR spectra of the same cells. A comparison between the results of this algorithm with the Bassan et al. (2017) algorithm for scattering correction that is freely available on the Internet was then conducted on two different cell lines, clearly showing the advantages of our algorithm, in terms of accuracy and precision. Therefore, this method can be viewed as a more suitable solution for scattering correction in cell investigations.