This dissertation presents the development, validation, and application of a suite of computational tools primarily designed to model and characterize the responses of radiation detection materials to ionizing photons, with extensions to material dose distribution and shielding analysis that broaden their applicability to a wide range of scientific and industrial fields. The suite includes Detector Materials Simulations (DETMATS), Photon Transport and Response Characterization Kit (P-TReCK), and GaussSpectraSwift. DETMATS, an Excel-based VBA application using the EPICS2023 library, is benchmarked for calculating the efficiency of high-energy photon detection materials against PHITS 3.31, showing minimal relative differences across a range of photon energies for NaI(Tl) and LaBr3(Ce) detectors. The P-TReCK tool, developed in C# for Windows, simulates real-time spectrum analysis, material dose distributions, and shielding performance. It includes a specialized version for simulating true coincidence summing (TCS) effects, significantly improving accuracy in close source-detector geometries and material-specific responses. For example, when radioactive material TCS effects are modeled, P-TReCK and PHITS both show a 33% overestimation in 60Co detection efficiency if TCS is not considered in close source-detector configurations, highlighting the significant accuracy improvement achieved by incorporating TCS. This tool also calculates TCS correction factors for common radionuclides, with results showing a relative difference of less than 1% compared to recent literature values, demonstrating excellent agreement. In terms of speed, P-TReCK outperformed MCNP5 (basic physics) by 3.1x, MCNP5 (detailed physics) by 3.5x, PHITS 3.33 (basic physics) by 3.8x, PHITS 3.33 (detailed physics) by 4.2x, and DETMATS by 13x. Case studies demonstrate the versatility of P-TReCK in simulating gamma-ray detectors and material dose distributions. Simulations of irradiated material phantoms, with customizable material composition and density, were benchmarked using water, yielding an average relative difference of less than 0.5% compared to PHITS 3.341 and MCNP5. Additionally, simulations of various shielding materials for attenuating ionizing photons from an adjacent soft tissue model yielded a 1% average relative difference against PHITS 3.341 for incident photon energies between 300 keV and 2,000 keV. GaussSpectraSwift, a Windows application developed in C#, streamlines the modeling of realistic detector response spectra by performing energy-resolution curve fitting and Gaussian energy broadening (GEB) for Monte Carlo detector simulation applications. It shows high equivalence with SciPy and improved accuracy in broadening detector response spectra, as indicated by reduced RMSE of its output broadened spectra compared to ideal spectrum benchmarks. This capability enhances the modeling of energy resolution for radiation detection materials by using fitted models that capture the material's intrinsic properties along with the effects of electronics noise, which influence the detector's energy response. Overall, this research presents a suite of validated software tools that enhance the analysis and characterization of radiation detection materials, dose distributions, and shielding simulations, with applications across various scientific and industrial fields.