This study analyzes conflict-induced displacement trends in the Democratic Republic of the Congo (DRC) from 2009 to 2022 using a quantitative approach based on autoregressive integrated moving average (ARIMA) modelling. Time-series data from the World Bank is utilized, with the number of internally displaced persons (IDPs) due to conflict and violence as the dependent variable, while autoregressive (AR) and moving average (MA) components serve as independent variables. Parameter estimation using conditional least squares (CLS) reveals that the MA(2) coefficient (0.999708) is positive and statistically significant, indicating that nearly 100% of current displacements are driven by external shocks or errors, which tend to reoccur approximately every two years. The estimated ARIMA (1, 2, 2) model is found to be covariance stationary and invertible, confirming its robustness for forecasting displacement trends. Based on these findings, we recommend addressing the root causes of conflict, strengthening early warning systems, enhancing humanitarian response mechanisms, investing in resettlement programs, and fostering regional and international cooperation to promote sustainable peace and stability in the DRC.