Herpes simplex virus 1 (HSV-1) has two routes of transmission in cell-culture: extracellular (cell-free) and direct cell-to-cell, but their relative contribution in host epidermal tissue, and how host responses impact each route is not yet understood. A powerful method for predicting virus dynamics is to use mathematical modelling, but applications to HSV-1 remain comparatively limited. Moreover, existing HSV-1 models often overlook the role of spatial dynamics and have rarely been validated against experimental data, reducing their accuracy in estimating key parameters. Incorporating experimentally derived values is therefore essential for reliable prediction of infection kinetics and for assessing how external factors influence virus propagation. Here, we present a newly developed spatial stochastic model of HSV-1 transmission that integrates experimental data from time-lapse imaging of GFP-tagged HSV-1 spread with mathematical simulations. The model incorporates both cell-to-cell and cell-free modes of transmission: infected cells transfer virus directly to neighbouring cells and can release virions into the extracellular space, where diffusion enables reinfection of the surrounding monolayer. Monte Carlo–based simulations combine experimentally derived rates with stochastic variability and spatial dependencies to predict infection dynamics, quantify the effects of viral replication and cell death, and evaluate how interferon modulates virus spread. Intriguingly, parameter fitting to experimental data reveals key kinetic differences among widely used HSV-1 strains and clinical virus isolates.  Going forward, this model will be used to recapitulate infection dynamics in 3D- skin rafts, evaluating the requirement for individual virus factors to gain further insights into how HSV-1 spreads within the human host.