Elastic light scattering measurements is one such promising approach that can be exploited to gather quantitative morphological information on bacterial colony growth.16–18 This follows because elastically scattered light from biological samples contain a wealth of morphological information, which if accurately extracted/quantified can serve as potential metrics for characterization of biological samples (including bacterial colony). Note that quantitative information on sample morphology can be obtained by either analyzing the angular variation or the wavelength variation of the elastic scattering signal.19–21 This would, however, involve appropriate modeling of light scattering in complex biological systems and development of suitable inverse analysis methods to extract/quantify the morphological information contained in the elastic scattering signal.19–21 In case of bacterial colony growth, the fractal nature of the colony is expected to have its characteristics impact the elastic scattering signal, via the corresponding self-similarity in the microscale fluctuations of local refractive index.22–26 Indeed, several studies have explored development of inverse light scattering models based on fractal-Mie or fractal-Born approximation of light scattering, for the quantification of the self-similarity of refractive index fluctuations in biological samples.22–26 These studies have revealed an inverse power law dependence of either the spectral or the angular variation of elastic scattering signal from such fractal biological structures, and the corresponding self-affinity has also been successfully quantified via the fractal micro-optical parameters (namely, the Hurst exponent, , or fractal dimension, ) derived using fractal-Born approximation.22–25 Such inverse light scattering based approaches are thus expected to provide quantitative information on the fractal growth of bacterial colony under different conditions. Since polarization properties of light scattered from samples contain additional microstructural and functional information on local organization, orientation of the scattering objects (which are otherwise hidden in polarization-blind optical measurements) and the combination of polarimetry with light scattering spectroscopy may yield complementary and useful information on the structural changes in the growth pattern of bacterial colonies. Specifically, the intrinsic sample polarization parameters, namely, the diattenuation, retardance, and depolarization coefficients27–29 and their wavelength variation may be exploited in combination with the fractal micro-optical properties, for quantitative assessment of the bacterial colony growth. However, extraction/quantification and unique interpretation of these intrinsic polarimetry characteristics in complex biological systems are severely confound by (1) simultaneous occurrences of several polarization effects and (2) by multiple scattering effects.27,28 The former effect causes lumping of several intrinsic polarimetry characteristics into the measurable polarization signal, leading to difficulties in their analysis and unique interpretation. While the latter effect, multiple scattering, not only causes extensive depolarization but also alters the polarization state of the residual polarization-preserving signal in a complex fashion.27,28 Note that both of these confounding effects are expected to be present in the bacterial colony samples. Recent studies have demonstrated that measurement of Mueller matrix (a matrix that describes the transfer function of any medium in its interaction with polarized light29,30) and its inverse analysis via polar decomposition can be explored to tackle these problems.31–33 The efficacy of such Mueller matrix decomposition approaches to delineate individual intrinsic polarimetry characteristics have also been validated in complex scattering media such as biological systems.34–37 In this paper, we have thus employed such a generalized method for polarimetry analysis in combination with light scattering spectroscopy (and fractal-Born approximation-based inverse light scattering model), for simultaneous extraction/quantification of the intrinsic polarimetry characteristics and the fractal micro-optical parameters of growing bacterial colonies to probe the structural changes taking place during the colony formations under different conditions.