In this paper, we analyze time series data for trends in poverty rates from 1994 to 2022 issued by the Central Statistical Organization. Then, we present a prediction of the poverty rates for 2023 and 2024 using the Expert Modeler method via SPSS software. Finally, we apply the least-squares method using the Eviews program to verify the model quality used in the prediction. The results revealed increased poverty trends. The prediction model results also predicted an increase in poverty rates in the future. The findings may aid the decision-makers in Yemen in rethinking their poverty-reduction strategies in light of the predicted model. This study provides relevant evidence for new insights into the extent and nature of poverty in least-developed countries, such as Yemen.