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Plant fungal pathogens are an increasingly common and costly threat to agricultural yields, resulting in wasted produce and the frequent use of fungicides. To enable more targeted use of fungicides, methods for detecting and identifying plant fungal infections in a rapid, low-cost, decentralized, and power-free manner are needed. CRISPR-based diagnostics have recently emerged as an effective tool for sensitive and specific pathogen detection in resource-limited settings. We present the preliminary designs of a CRISPR-based diagnostic for the soil-borne fungus Colletotrichum coccodes. Bioinformatics analysis led to the identification of four gRNA candidates targeting the ITS 1 and ITS 2 regions of C. coccodes for high specificity. The most promising gRNA was further screened and detection of DNA concentrations down to 500 pM without amplification are shown. This diagnostic for C. coccodes could be used in agricultural settings for rapid and cost-effective detection of fungal pathogens to enable high-yield sustainable agricultural practices.