Microplastic contamination has emerged as a critical environmental and public health concern, necessitating robust analytical methods for detection and characterisation. This chapter comprehensively reviews the application of Fourier Transform Infrared (FTIR) spectroscopy for microplastic analysis across environmental, food safety, and biomedical research domains. FTIR spectroscopy enables precise identification of microplastic polymers through their unique spectral fingerprints, with characteristic absorption bands distinguishing common plastics including polyethylene (PE), polypropylene (PP), polystyrene (PS), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The chapter examines various FTIR spectroscopy modes, including Attenuated Total Reflectance (ATR-FTIR), transmission, and reflectance FTIR spectroscopy, analysing their advantages and limitations for different sample types. Advanced techniques such as micro-FTIR (μFTIR) spectroscopy enable the detection of particles as small as 10–20 μm, while FTIR imaging provides spatial mapping capabilities for high-throughput analysis. Integration with artificial intelligence (AI) and machine learning approaches, including Convolutional Neural Networks (CNNs) and Principal Component Analysis (PCA), has enhanced identification accuracy and enabled automated classification processes. Applications span from riverine and marine microplastic monitoring to detection in seafood, drinking water, and human biological samples, demonstrating concentrations ranging from 1 to 302 particles per individual in various matrices. This establishes FTIR spectroscopy as an indispensable tool for microplastic research, providing both qualitative and quantitative analytical capabilities that support environmental monitoring, assessment of food safety, and human health evaluation in the context of global plastic pollution.