For herd certification programs tests for paratuberculosis typically are applied to all or part of the adult herd. Accuracy of herd classification is a function of the accuracy of the diagnostic tests employed, ie., sensitivity and specificity. Test sensitivity and specificity, however, are estimated experimentally on the basis of correct classification of individual animals. A more appropriate measure of herd classification accuracy is herd sensitivity (Hse) and herd specificity (Hsp). These measures of test accuracy when tests are applied to herds incorporate the number of animals in the population tested and the prevalence of the infection in the population. Recent studies discuss the factors affecting Hse and Hsp. In most herd certification programs, tests are applied to herds or flocks repeatedly, usually on an annual basis, to gain confidence in the infection-free status of the animal population (serial testing). Decisions regarding which tests to use, how many times to test the herd/flock, and how many animals to test each year are difficult to make and there are no statistical models on which to base decisions. Program design is always a compromise between the degree of confidence in the infection-free status of herds/flocks and the cost of the testing required. To facilitate design of regional or national herd certification programs for paratuberculosis a spreadsheet model was developed that incorporates test sensitivity, test specificity, number of animals tested in the population, testing costs for the herd, estimated herd/flock prevalence of paratuberculosis, and estimated mean within herd prevalence of paratuberculosis for infected herds. From these parameters, the probability that herds/flocks are not infected with M. paratuberculosis and cost to the herd owner was calculated after each successive annual test. The gain in certainty (post-test probability not infected minus pre-test probability not infected) is calculated in the spreadsheet as is the cost per unit gain in certainty. Lastly, for national program design purposes, the model calculates the cost to the state or country for implementation of the program used based on mean herd/flock size and numbers of herds/flocks in the state of country. The concepts behind the model will be described and the influences of altered assumptions of test accuracy or test selection will be demonstrated.