Due to the urbanization and vehicle growth in India, the accident rate was very higher especially in urban cities of India. In India on the year 2019 the country has reported around 1,51,000 deaths due to road accidents. The cause of road accidents may be due number of factors such as Road surface characteristics, geometric characteristics, human factors, vehicle characteristics and weather condition etc. Among the above factors the road surface characteristics such as macro and micro texture contributes to the vehicle skidding and causes of serious accidents, thus the above characteristics should be monitored and maintained in the road surface. In reality, monitoring the skid resistance of all roads and maintain the required skid resistance is very difficult. Hence in this study, the prediction model was developed for skid resistance and texture depth using regression technique for the optimum maintenance of urban roads surface characteristics such as skid resistance which mainly depends on the macro and micro texture of the pavement surface. In this study the vast network of roads with varying traffic characteristics, age and surfacing etc., the ease in data collection prompted to take the city of Chennai as the study area for the development of Skid resistance and texture depth prediction model. Models developed for using regression technique is found to be highly satisfactory. It is found out that factors influencing the progression of skid resistance are texture depth, traffic condition, age, variation of bitumen content from optimum and abrasion value, among which, the texture depth has greater influence on the skid resistance value. The model developed in this study can be utilized for the optimum maintenance of urban roads.