Manufacturing plants within Senegal's agricultural sector are increasingly adopting advanced technologies to enhance productivity and efficiency. A Bayesian hierarchical model was employed to assess adoption rates across different regions and types of manufacturing plants. The model accounts for variability within and between regions. The analysis revealed that adoption rates varied significantly by region, with a notable proportion (35%) higher in the northern part compared to the southern region. The Bayesian hierarchical model provided robust estimates of adoption rates, allowing for nuanced understanding of regional variations within Senegal’s agricultural sector. Further research should consider long-term impacts and potential policy recommendations based on these findings. Bayesian Hierarchical Model, Adoption Rates, Manufacturing Plants, Agriculture Sector, Senegal The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.