Forecasting of pavement condition and roughness is essential for optimization of pavement rehabilitation and treatment programs. This paper develops and presents a new set of Pavement Condition Index (PCI) and International Roughness Index (IRI) model for road networks in the city of St. John’s, Newfoundland. For this purpose, road sections that represent freeway, arterial, and collector road systems are selected. On these road sections, pavement distress survey was conducted after collecting video footage and photographs of the roads. In-field measurement of various distresses including rutting, load related and transverse cracking, potholes, and patching was performed in accordance with ASTM standard D6433-07. The survey data is then used to develop a PCI model. Results from the PCI model are validated using Pavement Service Rating (PSR) data obtained by surveying driver behavior in the city. IRI data is collected on all the road sections using a smartphone app called TotalPave. This data is then used to develop a new IRI forecasting model for the road networks. The IRI model output is validated using PCI and PSR data.