Cold Spray Additive Manufacturing (CSAM) uses high pressure gas to accelerate the metal powder particles to sufficiently high velocity (500m/s~1000m/s), facilitating material build-up upon impact with the target surface. The properties of the metal materials deposited by Cold Spray Additive Manufacturing (CSAM) processes are influenced by many factors including process parameters such as gas pressure and temperature, nozzle movement and tool path and more. Among these, Powder Size Distribution (PSD) emerges as a crucial determinant, significantly affecting attributes like porosity, residual stress, hardness, surface morphology, and the adhesive and cohesive strength of the deposited materials. To gain an in-depth understanding of PSD's impact on Ti-6Al-4V materials deposited by CSAM, we have employed comprehensive multiphysics and multiscale computational modelling and simulations. This simulation platform encompasses several components: (a) a virtual particle generator that creates a powder supply with varying PSDs, controlled by key parameters; (b) a CFD model predicting velocity and temperature of thousands of in-flight particles; (c) a data exchange module for transferring results from CFD to FEM models; (d) a single particle impact FEM model for determining particle bonding criteria; (e) a model for estimating deposition efficiency; (f) a multiple particle impact FEM model for simulating material deposition; and (g) an FEM model for estimating the strength of the deposited material. These computational models are instrumental in understanding defect generation, residual stress evolution, and assessing the tolerance and sensitivity of PSDs on material properties. The models were validated through three sets of experiments with different PSDs. These experiments involve comprehensive microstructure characterisation using SEM and EBSD, particle velocity measurements during production, residual stress, and material strength assessments. Both computational and experimental findings underscore the significant influence of PSD in CSAM processes, offering insights into potential PSD optimizations or customizations for desired material properties.