Accurate estimation of the age of bloodstains—also known as time since deposition (TSD)—remains a critical yet unresolved challenge in forensic science. Traditional methods, such as visual inspection and colorimetric assays, offer limited temporal resolution and are highly sensitive to environmental variability. In contrast, recent advancements have introduced a diverse array of analytical techniques, including ultraviolet-visible (UV–Vis) spectroscopy, attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy, and fluorescence-based methods. These tools enable the detection of chemical and structural changes in hemoglobin and other biomolecules as bloodstains age. Concurrently, molecular approaches—such as mRNA degradation profiling, DNA methylation analysis, and microRNA (miRNA)-based models—have shown promise in providing stable, time-sensitive biomarkers. The integration of machine learning, particularly through neural networks and random forest models, further enhances the accuracy and field applicability of these methods. Portable devices, including handheld near-infrared (NIR) spectrometers and mobile imaging systems, are now being developed for real-time, on-site analysis. Despite these advancements, challenges persist in the form of environmental sensitivity, substrate dependency, lack of standardization, and legal admissibility. This paper reviews the current landscape of bloodstain aging techniques, highlights their strengths and limitations, and outlines future directions for developing robust, admissible, and field-ready solutions for forensic timelines.