The expanding adoption of organic fertilizers in sustainable agriculture necessitates reliable and rapid quality assessment methods to ensure optimal nutrient delivery and environmental safety. Traditional laboratory-based compost characterization techniques, while accurate, are time-consuming, destructive, and limited in spatial coverage, hindering real-time process control and large-scale quality monitoring. Hyperspectral imaging (HSI) has emerged as a transformative non-destructive technology that captures both spatial and spectral information across hundreds of contiguous wavelength bands, enabling detailed characterization of compost chemical composition, maturity status, and nutrient content. When integrated with machine learning algorithms, HSI systems can automate the detection and quantification of key quality parameters including organic carbon, nitrogen, phosphorus, moisture content, and maturity indices without sample preparation or chemical reagents. This review examines the principles, applications, and computational frameworks underlying smart compost quality monitoring systems that combine hyperspectral imaging with advanced data analytics. We analyze spectral signatures associated with compost constituents, evaluate machine learning models for predictive nutrient estimation, and discuss automated classification approaches for maturity grading. The integration of these technologies offers significant advantages for precision agriculture, enabling site-specific organic fertilizer management, reducing environmental pollution from improper compost application, and supporting circular economy initiatives in agricultural waste recycling. Despite considerable progress, challenges remain in standardizing acquisition protocols, improving model transferability across different compost types, and reducing system costs for widespread adoption. Future developments in deep learning architectures, sensor miniaturization, and cloud-based decision support platforms promise to enhance the accessibility and impact of intelligent compost monitoring technologies.