It was found that ischemic stroke (IS) was associated with abnormal platelet activity and thrombosis. However, the potential significance of platelet-related genes (PRGs) in IS still needs to be more thorough. This study extracted IS-related transcriptome datasets from the Gene Expression Omnibus (GEO) database. The target genes were obtained by intersecting the differentially expressed genes (DEGs), the module genes related to IS, and PRGs, where the key genes of IS were screened by two machine learning algorithms. The key genes-based diagnostic model was constructed. Gene set enrichment analysis (GSEA) and the immune microenvironment analyses were analyzed targeting key genes in IS. The co-expression, TF-mRNA, and competitive endogenous RNAs (ceRNA) regulatory networks were constructed to reveal the potential regulation of key genes. Potential drugs targeting key genes were predicted as well. Totals of eight target genes were obtained and were associated with immune-related functions. Four platelet-related key genes were acquired, which were related to immunity and energy metabolism. The abnormal expressions of DOCK8, GIMAP5, ICOS were determined by the quantitative real-time polymerase chain reaction (qRT-PCR), and the significant correlations among these key genes were identified. Notably, hsa-miR-17-3p, hsa-miR-3158-3p, hsa-miR-423-3p, and hsa-miR-193a-8p could regulate all key genes at the same time. In addition, Caffeine, Carboplatin, and Vopratelimab were the targeted drugs of these key genes. This study identified four platelet-related key genes of IS, which might help to deepen the understanding of the role of platelet-related genes in the molecular mechanism of IS.