To aid tissue polarimetry in successful implementation of polarization gated optical imaging and for quantitative determination of intrinsic tissue polarimetry characteristics, accurate forward modeling is enormously useful. This helps in gaining physical insight, designing, and optimizing experiments, and analyzing/interpreting the measured data. The use of electromagnetic theory with Maxwell's equations is the most rigorous and best-suited method for polarimetry analysis, at least in clear media with well-defined optical interfaces. However, unlike optically clear media, tissue is a turbid medium possessing microscopically inhomogeneous complex dielectric structures (macromolecules, cell organelles, organized cell structures, blood and lymphatic networks, extra-cellular matrix, interstitial layers, etc.). Due to the ensuing complexity, the Maxwell's equations approach for polarized light propagation in such a complex turbid medium is impractical and is not presently feasible.11,50 Instead, light propagation through such media is often modeled using the radiative transport theory.11,50- 51 Although the scalar radiative transport theory and its simplified approximation, the diffusion equation, has been successfully used to model light transport in tissue (specifically light intensity distribution in tissue volume, diffuse reflectance, etc.), both are intensity-based techniques, and hence typically neglect polarization.51 Alternatively, the vector radiative transfer equation (VRTE), which includes polarization information by describing transport of the Stokes vectors of light (photon packet) through a random medium,11,51 has been explored for tissue polarimetry modeling. However, solving the VRTE in real systems is rather complex. A wide range of analytical and numerical techniques have been developed to solve VRTE, namely, the small angle approximation, the transfer matrix, the singular eigenfunction, the adding-doubling, the discrete ordinates, the successive orders, and the invariant embedding methods.11,51 Unfortunately, these are often too slow and insufficiently flexible to incorporate the necessary boundary conditions for arbitrary geometries and arbitrary optical properties as desirable in case of tissue. A more general and robust approach is the Monte Carlo (MC) technique, as described in greater detail below. First, we present a brief overview of some of the simpler analytical approximations developed to deal with depolarization of multiply scattered waves in turbid medium. These are useful for understanding the mechanisms of depolarization of light in turbid media, for performing rough estimates and order-of-magnitude calculations, and for optimizing the polarization gating schemes for tissue imaging.