Peroxisomal or glycosomal membrane proteins (PMPs) depend on specific signal sequences, known as membrane peroxisomal targeting signals (mPTS), which are recognized by the cytosolic chaperone and import receptor PEX19. Computational prediction of PEX19-binding sites is a critical tool for identifying both known and novel PMPs and for advancing our understanding of the biogenesis of peroxisomes or glycosomes across diverse organisms, including humans, plants, fungi, and members of the Euglenozoa. PEX19-binding site prediction, including mPTS, is a computationally intensive process with broad applications, from identifying PMPs involved in essential cellular functions to uncovering pathogenic proteins in infectious agents, such as viruses, which interfere with the biogenesis or function of host cell peroxisomes. A web-based tool developed by Rottensteiner et al. previously enabled the prediction of PEX19-binding sites (PEX19BS), but it has become inaccessible, creating a significant gap for researchers aiming to identify and analyze these critical targeting motifs efficiently. To address this limitation, we have restored accessibility to a previously developed matrix-based prediction tool, now available as an open-access Google Colab notebook. This implementation enables efficient analysis and export of results, reinstating a valuable resource for studying membrane targeting in the biogenesis of peroxisomes and glycosomes.