Land surface temperature (LST) is listed as an essential climate variable (ECV) and supports quantitative estimates of the energy budget while serving as a proxy for measuring the effects of climate change and extreme events. Forested areas are considered a major land unit impacted by temperature rise; therefore, thorough monitoring is mandatory. An accuracy assessment of the LST of forests must consider their directional anisotropy (DA). This latter can be well depicted by thermal infrared (TIR) radiative transfer models, but the problem is complex for forests because many of the shaded areas generate multiscale gradients of temperature. In this paper, we adapted a mature and widely used visible and near-infrared (VNIR) radiative transfer model called forest reflectance and transmittance (FRT) to enhance the characterization of the DA of forest temperature. In the FRT model, the vertical heterogeneity of the forest is quantified by using the discrete elements of multilayer scene components (i.e., the tree crown, trunk, understory vegetation, and soil), thus inferring vertical thermal gradients. The Planck function and spectral-invariant theory are considered to assess the thermal emissions of the scene components and their multiple scattering processes. The FRT model is validated using directional forest brightness temperatures (BT) measured from an unmanned aerial vehicle (UAV) and simulated by using the three-dimensional ray-tracing LESS (large-scale remote sensing data and image simulation framework over heterogeneous 3D scenes) model. The results show that FRT behaves reliably since the root mean square error (RMSE) is lower than 1.0 °C for UAV measurements obtained at 09:20 and 13:10 and with coefficients of determination (R 2 ) larger than 0.74 and 0.56, respectively; these results are better than the simulated results by existing models. Moreover, the comparison with ray-tracing simulations was also deemed satisfactory. According to the analysis, large variations in BT DAs may appear for different forests and seasonal changes staged by structural and thermal stratification, thus indicating the necessity of using the FRT model for complex and dynamic forest canopies.