Various forms of light-scattering measurements and spectroscopy are showing promise as a biopsy-free means to measure the size distribution of nuclei and associated scattering as an indicator of preinvasive neoplasia and malignancy.1–12 Many of these techniques require or would benefit from accurate models of light transport near the point of entry. Computational models of light transport including Monte Carlo simulations13–16 and numerical implementations of the radiative transport equation17–20 are typically too computationally burdensome to be used for applications where rapid analysis is important. Analytical solutions have primarily been restricted to diffusion-theory approximations21,22 or slightly higher order corrections,23–27 which are inaccurate near the point-of-entry and when absorption is high or comparable with scattering coefficients. Unfortunately, accurate analytical models of light propagation in tissue near the point-of-entry and for cases where absorption is high or comparable with scattering have been difficult to obtain. Recently, Vitkin et al.28 described an elegant phase-function corrected (PFC) diffusion approximation to the radiative transport equation which permitted an analytical description of a pencil beam normally incident on a semi-infinite turbid medium. In this paper, we extend their work to include a pencil beam obliquely incident on a semi-infinite turbid medium, and investigate the accuracy of the models by comparing them with Monte Carlo simulations. The case of oblique incidence is of noteworthy importance as a number of techniques rely on angled illumination, including oblique incidence reflectometry (OIR) and1–6,29–31 angled low-coherence interferometry,32–38 among others.11 In this article, we focus on the applications of OIR, a technique that has seen great success in some clinical studies.6,31 In this technique, diffuse reflectance from an obliquely incident beam is recorded and compared with diffusion models of light transport to estimate the tissue optical properties. However, to obtain accurate estimates, the sensing footprint (defined here as the minimum circular area containing source and detector fibers) generally needs to be larger than a few transport mean-free paths to reliably estimate the centroid of diffuse-reflectance, with some recent exceptions.39,40 Still, the probe sizes in such recent work are too large to be used for micro-endoscopic applications, which would enable a broader range of clinical applications beyond dermatology. Smaller-footprint probes require improved light-propagation models and inversion schemes for diffuse reflectance close to the point of entry. Recent works39,40 leverage the scalable Monte Carlo method,41 which can scale the amplitudes and coordinates of the time-resolved diffuse reflectance of a reference simulation to transform to an effectively different turbid medium. The steady-state diffuse reflectance is then found by integrating over time. This method avoids iterative application of Monte Carlo simulations, and permits small-footprint sensors. Our work provides an alternative approach that avoids stochastic variability associated with Monte Carlo results, and is fast, accurate, and based on analytical models. With future efficient algorithm implementation, the speed of inversion afforded by the analytical models could enable development of microprobes with real-time feedback for tumor margin resection guidance, and clinical classification of suspected tumors and assessment of precancers.