Test data compression is widely employed in scan designs to tackle high test data volume and test time problems. Given the number of scan-in pins available in the ATE, architectural decisions regarding the number of internal scan chains directly impact the compression level attained. While targeting an aggressive compression level by increasing the number of internal scan chains would reduce the test data volume per encodable pattern, the cost of applying more patterns serially, to restore the coverage loss, offsets the compression benefits. Therefore, a predictive analysis is necessary to determine the best possible compression configuration, enabling the designers to make DfT architectural decisions early on in the design cycle to minimize test costs. In this paper, we propose a suite of predictive techniques geared towards projecting test cost for any given compression-based scan configuration. T he appropriate technique is selected by designers based on which stage the design is in, the design abstraction and the amount of information available, the permissible computational complexity of the techniques, and the accuracy of the projected optimal compression ratio.