This paper aimed at utilizing GIS software in calculating pavement condition index )PCI( values, using four different interpolation methods: IDW, spline, trend and kriging. The case study covers four major streets in Nablus city with a total length of about 6.50 km. The PCI values were calculated using the ASTM conventional method. The four streets were divided into equal 100- meter sections. The PCI values were also calculated for each point of defect in both directions of the streets. The results of the four methods (point by point of defects) were compared manually with the conventional method (ASTM procedure). The results showed that the spline method had a strong correlation with the conventional method in terms of multiple R and R-square calculation (multiple R for left 0.918, right 0.947 and R2 for left 0.843, right 0.897). This method also fitted the data better than the other methods, as seen from the linear regression model results, in addition to producing the minimum error value. The results indicated that by identifying the PCI value, it would be possible to select the proper pavement maintenance and corresponding cost for each point of defect. This in turn would help in prioritizing pavement sections. KEYWORDS: Pavement condition index (PCI), GIS, Interpolation, Distress, Maintenance, Spline.