The global production and disposal of plastics have led to pervasive contamination of natural environments, representing considerable risks to human health and ecosystems. This study introduces a novel oil-based method for extracting microplastics (MPs) from water samples, with a focus on optimizing extraction conditions and improving the quality of MPs identification using Raman spectroscopy. Various parameters including the type of oil, salinity, temperature, air incorporation, and washing solvent were investigated to enhance extraction efficiency and spectroscopic identification accuracy. Sunflower oil emerged as the preferred extraction medium due to its compatibility with Raman spectroscopy, offering high recovery efficiencies for polypropylene (PP) and polystyrene (PS). Additionally, ethanol was identified as a better washing solvent compared to hexane, improving MPs identification. The optimised method was then applied to environmental water samples, revealing matrix effects and challenges with digestion step. Despite these challenges, the proposed method represents a significant advancement in microplastic analysis, offering reliable detection and quantification in aquatic environments. Further optimisation is needed to address matrix effects and improve recovery efficiency, especially for smaller microplastics.