Predictive Model for Food Insecurity in Nigeria Using Deep Learning Technique Emmanuel A. Dan 1 and Bolanle F. Oladejo 2 1 Department of Computer Science, Faculty of Science, University of Uyo, Uyo 520001, Nigeria. emmanueldan@uniuyo.edu.ng 2 Department of Computer Science, Faculty of Science, University of Ibadan, Ibadan 200001, Nigeria. Oladejobola2002@gmail.com Abstract The robust nature of Artificial Intelligence (AI) technologies has displayed a continuous momentum in the interdisciplinary problem-solving spectrum; one of such is food insecurity. Food insecurity is a global growing challenge that requires earnest attention in some parts of the world; that is commonly determined through surveys peculiar to the socioeconomic factors of a country. The peculiarity to socioeconomic characteristics related to food insecurity of a country, and sparse or limited predictive models based on data-driven technology, particularly for Nigeria’s case has led to models for predicting food insecurity that is limited in Nigerian factors. Thus this paper presents a Deep Neural Network (DNN) model for food insecurity prediction in Nigeria among households at the subnational level peculiar to the socioeconomic characteristics of the country. The method used in this study is based on a classification approach using Multi-Layer Perceptron DNN (MLP-DNN) on open data from Nigeria - General Households Survey (GHS) on households’ standard of living with respect to food insecurity, from worldbank and National Bureau of Statistics (NBS) over a period of four years to develop a model to predict the state of the household in the context of Nigeria as food secured or food insecure. The performance of the model displayed accuracy of approximately 98%, outperforming the logistic model and the Artificial Neural Network model with an accuracy of approximately 93% respectively, which were developed alongside for performance evaluation based on confusion matrix analysis. However, these models comparably performed poorly in some other countries with different measures for socioeconomic characteristics. Keywords: Food insecurity, Food Security, Socioeconomic Characteristics, Nigerian peculiarities, Predictive model 1.0 Introduction The sphere of computing technology is interdisciplinary in nature. Even so, notwithstanding the massive applications to complement human efforts in problem-solving, some areas concerning our welfare have received little or no attention in some parts of the globe; and one of such is the food insecurity crisis. Currently, food insecurity is the predominant factor behind acute hunger, starvation, malnutrition, and deteriorating health status among many households in Nigeria (Etim et al., 2017; Ajie and Uche, 2019). In compliance with the United Members States’ agenda for Sustainable Development with 17 Sustainable