An association between RNA degradation and the time since deposition (TsD) of a biological stain has previously been demonstrated. Despite the encouraging results obtained with several RNA markers, the variability in results between individuals and analytical approaches limits the method's application in casework. The incorporation of multiple markers into a single prediction model could enhance estimation accuracy. Typically, real-time qPCR has been the primary analytical platform for these studies. However, qPCR requires high sample volumes and involves numerous pipetting steps when analysing multiple markers, increasing the risk of errors. In this study, we aim to optimize the TsD analysis by combining six targets in three mRNA markers (S100A12, LGALS2 and CLC) in a PCR multiplex and transitioning the analysis platform from qPCR to capillary electrophoresis (CE). This collaborative effort between the Department of Forensic Research at Oslo University Hospital (Laboratory 1) and the Zurich Institute of Forensic Medicine (ZIFM, Laboratory 2) analysed a total of six sample sets, spanning a period of 0 days up to 1.5 years (551 days), along with a broad set of test samples including different carrier materials. Furthermore, a machine learning model was employed to predict the age of bloodstains, aiming to enhance the precision and reliability of TsD estimations.