Deterioration models for pavement surface distresses have been developed using probabilistic modelling approaches. The condition data is collected using visual inspection surveys. Distress data used in the modelling include cracking, texture loss and stone loss of different pavement surfacing types. The latter includes dense graded asphalt, open graded asphalt, ultra-thin asphalt, sprayed/chip seal and geotextile seal (chip seal with geotextile underlay). Probabilistic modelling approaches used include logistic regression and Markov chains (MC). The two variables used in the modelling are distress rating and surface age. These models are to be used for network level management. For the network modelled herein, logistic models are found to provide predictions that are comparable with actual average condition data at different age values. It is also observed that predictions of most MC models are higher than predictions of logistic models and actual average data.