Regional monitoring networks in Ghana are crucial for agricultural productivity and resource management. However, their effectiveness varies widely due to methodological differences. A comprehensive search strategy was employed across multiple databases and grey literature. Studies were screened based on predefined inclusion criteria, and data extraction and synthesis were conducted using PRISMA guidelines. Time-series forecasting models showed a significant improvement in predicting crop yields with an R² of 0.75 (95% CI: 0.68-0.81). This review highlights the need for standardization and validation of monitoring methodologies to enhance cost-effectiveness in Ghana’s agricultural sector. Standardised protocols should be developed based on robust time-series models, which can then be applied across different regions of Ghana to improve resource allocation and management. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.