Kriging is one of the important interpolation methods in geostatistics, which has been widely applied in engineering project. In this paper, we present an efficient method for the parallelization of universal Kriging interpolation on shared memory multiprocessors. By using OpenMP directives, we implement a portable parallel algorithm, which enables an incremental approach to add parallelism, without modifying the rest part of sequential code. To achieve optimal performance, the parallel grain size has been considered and analyzed. Numerical experiments have been carried out on two multicore windows workstations, the results of which demonstrate this method could enhance the overall performance significantly.