Kernel coupling quantifies the interaction between adjacent and chains of kernels in an application. A kernel can be a loop, procedure or file. In our previous work, we used the kernel coupling values to identify how to combine the execution times of the individual kernels that compose the application to predict the execution time of the full application. The results of this previous work using the NAS Parallel Benchmark SP demonstrated that the use of coupling values resulted in very good predictions with average errors in the range of only 1.18% in contrast to simply summing the execution times of the kernels that resulted in average errors in the range of 20.54%. The major concern with the coupling values is the fact that values are needed for each different problem size, number of processors and machine. In this paper, however, we explore the ability to reuse coupling values. In particular, we explore the reuse in terms of the three dimensional space consisting of the following axes: number of processors, problem size and system architecture. The experimental results indicate that when considering parallel systems, with increasing number of processors and problem sizes, we found clear transitions with the coupling values resulting in the ability to reuse values. Further, reusing coupling values is feasible on classes of systems such as clusters, distributed shared memory and other distributed memory systems.