This study investigates the epidemiological trends and dynamics of typhoid fever in North-Central Nigeria by analyzing cases recorded at Grimard Catholic Hospital, Anyigba, from 2015 to 2024. Monthly time series data of positive and negative typhoid tests were examined using descriptive and inferential statistics to identify patterns, trends, and seasonal variations. Positive cases consistently outnumbered negative ones, indicating a sustained disease burden. Time series decomposition revealed clear seasonal structures and a slight downward trend, suggesting gradual improvements in public health conditions. Stationarity tests confirmed the data’s suitability for modeling. Forecasting methods, including ARIMA, exponential smoothing, and Fourier series, captured the underlying trends effectively, with ARIMA providing the strongest predictive performance. Seasonal peaks during rainy months underscored the influence of environmental factors on transmission dynamics. These findings offer critical insights into typhoid fever patterns in North-Central Nigeria and provide a statistical basis for designing targeted interventions and strengthening regional public health planning.