The recent renaissance of enzyme-linked immunospot (ELISPOT) assays largely is the result of advances in image analysis. Information on the frequency of antigen-specific T-cells and also on the secretion rate of the individual cells is captured in spots generated using this technique. Although the overall assessment of ELISPOT results can be conducted visually, this is inevitably subjective, inaccurate, and cumbersome. In contrast, objective, and accurate measurements are fundamental to good science. Validated image analysis algorithms and procedures, therefore, have become critical for elevating the quality of ELISPOT assays results. As cytokine and granzyme B ELISPOT assays become the gold standard for monitoring antigen-specific T-cell immunity in clinical trials, the pressure increases to make ELISPOT analysis transparent, reproducible and tamperproof, complying with Good Laboratory Practice and Code for Federal Regulations Part 11 guidelines. In addition, ELISPOT assays in clinical and basic science settings frequently require high degrees of throughput, thus further raising the need for advanced data management and statistical analysis. The ImmunoSpot software port-folio has been specifically designed to meet all these needs, using the techniques described in this chapter.