Real-time biomolecular monitoring requires biosensors based on affinity reagents, such as aptamers, with moderate to low affinities for the best binding dynamics and signal gain. We recently reported Pro-SELEX, an approach that utilizes parallelized SELEX and high-content bioinformatics for the selection of aptamers with predefined binding affinities. The Pro-SELEX pipeline relies on an algorithm, termed AptaZ, that can predict the binding affinities of selected aptamers. The original AptaZ algorithm is computationally complex and slows the overall throughput of Pro-SELEX. Here, we present Apta FastZ, a rapid equivalent of AptaZ. The Apta FastZ algorithm considers the spare nature of the sequences from SELEX and is coded to avoid unnecessary comparison between sequences. As a result, Apta FastZ achieved a 10 to 40-fold faster computing speed compared to the original AptaZ algorithm while maintaining identical outcomes, allowing the bioinformatics to be completed within 1-10 h for large-scale data sets. We further validated the affinity of myeloperoxidase aptamers predicted by Apta FastZ by experiments and observed a high level of linear correlation between predicted scores and measured affinities. Taken together, the implementation of Apta FastZ could greatly accelerate the current Pro-SELEX workflow, allowing customized aptamers to be discovered within 3 days using preselected DNA libraries.