Dissertation (MSc Statistics)This study examined the modelling for maize prices using Autoregressive Integrated Moving Average (ARIMA) models so as to determine the most efficient and adequate model for analyzing the maize monthly prices at the Gairo market in Morogoro Region, Manyoni market in Singida Region and Kibaigwa market in Dodoma Region. The results indicate that ARIMA (1, 1, 4) model is the most adequate and efficient model for Gairo market, ARIMA (2, 1, 3) model is the most adequate and efficient mode1 for Manyoni market and ARIMA (2, 2, 3) model is the most adequate and efficient model for Kibaigwa market. This was determined by comparing the various model selection criteria and the diagnostic tests for various models among them Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) and Mean Absolute Percentage Error (MAPE). Time-series analysis was done using STATGRAPHICS, EXCEL, R software and SAS JPM. The forecast results suggest that there are expectations of increasing maize prices in Manyoni market from July-2018 to March-2019, the maize prices in Kibaigwa market are also expected to increase with time from January 2018 to February 2019 and the maize prices at Gairo market are expected to keep on increasing with time from July 2018 to May 2019. A better understanding of maize prices situation and future prices will enable producers and consumers to make the right choices concerning buying and selling arrangements. Hence, the government should take appropriate actions to make sure that both producers and consumers are earning the profit.