The skid resistance of asphalt pavement is a major characteristic that determines the driving safety on a road, especially under wet surface conditions. Skid resistance is primarily a function of the microtexture and macrotexture of a pavement surface. Microtexture is influenced by aggregate surface characteristics and is required to disrupt the continuity of surface water film and attain frictional resistance between the tire and the pavement surface. Macrotexture is affected mostly by mixture design or aggregate gradation and contributes to skid resistance by providing drainage paths of water that can be otherwise trapped between a tire and a pavement surface. The increase in macrotexture contributes to preventing hydroplaning and improving wet frictional resistance, particularly at high speeds. While much research has been conducted in the past to identify material factors that affect skid resistance, there is still a need to develop a model for predicting asphalt pavement skid resistance as a function of mixture characteristics and traffic level. The purpose of this study was to develop such a model based on extensive laboratory experiments and field measurements involving different mixture types and aggregate sources. The model incorporates functions that describe the resistance of aggregates to polishing and aggregate size distribution. The aggregate resistance to polishing was quantified by measuring aggregate texture using the Aggregate Imaging System (AIMS) before and after polishing in the Micro-Deval device. The analysis in this dissertation demonstrates how this model can be used to design mixtures and classify aggregates that provide desirable skid resistance levels.