MicroRNAs (miRNAs) have emerged as valuable biomarkers for the identification of forensic body fluids due to their stability and tissue specificity. However, the limited quantity of body fluid at crime scenes often hampers the accuracy of miRNA-based detection methods. In this study, we developed a triplex reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay system that enables the simultaneous detection of three miRNAs, improving throughput and efficiency while overcoming challenges in forensic investigations. First, the primers and probes of the miRNAs were redesigned to meet multiple detection requirements on the basis of a previous study in which five types of body fluid-specific miRNAs and internal genes (miR-451a, miR-891a-5p, miR-144-5p, miR-203a-3p, miR-223-3p and miR-320a-3p) were screened in a laboratory. The primer and probe concentrations, premix concentration and annealing temperature were subsequently optimized to establish a triplex RTqPCR assay system. This system enables the simultaneous reverse transcription of six miRNAs from a single sample, followed by two separate triplex amplification reactions to quantitatively analyze all six miRNA markers. The amplification efficiency, primer cross-reactivity, repeatability, triplex detection and single detection results of the system were subsequently analysed, and a prediction model was constructed by combining the sample data with a kernel density estimation (KDE) method. Finally, the ability of the detection method to identify body fluids was further verified with authentic samples. The results demonstrate that the optimized triplex RTqPCR assay system achieves the same detection performance as the single detection system, but is faster and more cost-effective. This technology is especially suitable for the detection of trace body fluid stains left at crime scenes and effectively solves the contradiction between the requirements of repeated RTqPCR detection of traces and multiple sample sizes. In addition, the body fluid identification model, which was established by the data obtained from the triplex RTqPCR system combined with KDE, was successfully applied to predict and identify simulated samples and actual samples. This system provides an effective tool for the identification of suspicious body fluids and lays the foundation for further research on multiplex RTqPCR assay systems and the construction of more accurate data models.