Background: In 1946, nearly 90% of patients diagnosed with metastatic Testicular Germ Cell Tumor (TGCT) succumbed to the disease within a year. In the present day, over 90% of such patients are successfully cured. However, there is a remaining 10% of patients have tumors that consist of chemotherapy-resistant forms of TGCT, such as yolk sac tumors and teratomas. This underlines the need for developing biomarkers that can guide the choice between additional chemotherapy and surgical intervention. MicroRNAs (miRNAs), non-coding RNA molecules that control post-transcriptional modifications, have shown promise in identifying TGCTs. Research has particularly highlighted the overexpression of miR-371a-3p and miR-375-3p in TGCTs. Nevertheless, these miRNAs are not effective in distinguishing between teratomas and other TGCT types. The Cancer Genome Atlas (TCGA), a publicly accessible database, offers clinical and miRNA data on various tumors, including TGCTs. Our objective is to leverage TCGA to identify miRNAs that can be used to classify TGCTs containing teratomas from those that do not. Methods: Between 2001 and 2013, TCGA gathered a total of 135 primary TGCT samples. We group these tumors into those without teratomas and those with any teratomatous components. We used EdgeR, a Bioconductor package designed for differential expression analysis of RNA that accounts for both biological and technical variation. A false discovery rate of less than 1e-8 was applied. A heatmap was generated to display the hierarchical clustering of differentially expressed miRNAs. Results: Based on the above cut-off, a panel of 50 miRNAs of differentially expressed miRNA were used to generate a hierarchical clustering that showed clear clustering between the two groups. Notably, tumor suppressor miRNAs such as hsa-mir-203a, hsa-mir-199, and hsa-mir-152, which are usually downregulated in non-teratoma TCGT, are overexpressed in teratomas. Other miRNA including hsa-mir-146a and hsa-mir-3607, which are downregulated tumor suppressors for non-TCGT are also downregulated in teratomas but not in teratoma-free TGCT. Conclusions: Despite the high cure rate for TGCTs, tumors containing chemotherapy-resistant teratomas still contribute to elevated mortality rates. Utilizing TCGA data, we identified a set of miRNAs that are effective in distinguishing between teratoma-containing and teratoma-free TGCTs. This miRNA panel has the potential to inform decisions related to surgical treatment plans and provide further insight into the biology of the disease.