Canopy radiative transfer (RT) modeling is critical for the quantitative retrieval of vegetation biophysical parameters and has been under intensive research over the decades. RT models of discontinuous canopies, such as three-dimensional (3D) RT models, posed challenges for the early one-dimensional (1D) hypothesis. Although 3D RT models have higher accuracy, theoretically, they suffer from two problems: detailed scene parameters and complex computational steps. To overcome these problems, the stochastic radiative transfer (SRT) theory, which is known to have the accuracy of 3D RT while being as simple as 1D RT, has been adapted from atmospheric research to the study of vegetation canopies. While the SRT model has been adopted into the operational production of vegetation parameters, its accuracy needs further improvement because of the insufficient consideration of hotspot effects. Additionally, the evaluation and validation of SRT process are still preliminary, which hinders its further development and application. To provide the community with missing information and a scientific basis for subsequent model improvement, we modified, evaluated, and validated the SRT model in this study. First, we proposed the new version of SRT model to better achieve the coupling of SRT process and hotspot effect by dividing the previous SRT into four subproblems. Then, we evaluated the performance of the modified SRT by comparing multiple intermediate variables in the SRT process with 3D computer simulations, and analyzed the model sensitivity to key input parameters as well as the spatial distribution and conservation of radiation energy. Our findings reconfirmed that the SRT theory can well describe the radiation regime of discontinuous canopies with balanced efficiency and accuracy. Moreover, the newly proposed coupling scheme of hotspot effect further improves the model performance in the hotspot regions. Finally, the unmanned aerial vehicle (UAV) observations served as a reference to validate the modeled canopy reflectance, which shows a high concordance. These results provide a detailed theoretical basis for applications and further improvements of the SRT model.