Understanding the causal factors associated with human/livestock-large carnivore conflict and distribution of conflict risk is key to designing effective preventative and mitigation strategies. Spatial modelling of human-carnivore conflict has recently gained traction, and predictive maps have become a great tool to understand the distribution of present and future conflict risk. However, very few such studies consider scale and use appropriate spatial modelling tools. We aimed to understand the ecological correlates of human-tiger (Panthera tigris) conflict, predict livestock predation risk by reintroduced tigers in Panna Tiger Reserve, Central India and understand the prey-predator dynamics behind the conflict. We modelled livestock kill as a function of various tiger relevant ecological variables at multiple scales employing spatially explicit statistical tools. As a first step, we used geostatistical modelling to create raster layers of covariates (prey, cover, human activities), following which we did univariate scaling. We then modelled livestock loss by tiger using a geoadditive model. Employing this model, we predicted and mapped conflict risk probabilities within our study site. It was found that prey and shrub cover both selected at a fine scale, were key ecological determinants of human-tiger conflict. Prey showed an inverse relationship while shrub showed non-linear relationship with livestock predation. Which lead us to conclude that in habitats where optimum ambush cover is available but prey presence is low at fine-scale, carnivores are more likely to depredate domestic livestock since livestock have lost most of their anti-predator behaviours. Livestock kill by tiger is thus a culmination of predator choice and foraging tactics, and prey vulnerability and defence mechanism. The spatially explicit predation risk map produced in this study can guide adequate human-tiger conflict prevention measures.