Soil moisture retrieval from polarimetric synthetic aperture radar (SAR) imagery over forested terrain is quite a challenging problem, because the radar backscatter is affected by not only the moisture content, but also by large vegetation structures such as the trunks and branches. Although a large number of algorithms which exploit radar backscatter to infer soil moisture have been developed, most of them are limited to the case of bare soil or little vegetation cover that an incident wave can easily reach the soil surface without serious disturbance. However, natural land surfaces are rarely free from vegetation, and the disturbance in radar backscatter must be properly compensated to achieve accurate soil moisture measurement in a diversity of terrain surfaces. In this paper, a simple polarimetric parameter, co-polarized backscattering ratio, is shown to be a criterion to infer moisture content of forested terrain, from both a theoretical forest scattering simulation and an appropriate experimental validation under well-controlled condition. Though modeling of forested terrain requires a number of scattering mechanisms to be taken into account, it is essential to isolate them one by one to better understand how soil moisture affects a specific and principal scattering component. For this purpose, we consider a simplified microwave scattering model for forested terrain, which consists of a cloud of dielectric cylinders as a representative of trunks, vertically stood on a flat dielectric soil surface. This simplified model can be considered a simple boreal forest model, and it is revealed that the co-polarization ratio in the ground-trunk double-bounce backscattering can be an useful index to monitor the relative variation in the moisture content of the boreal forest.