Bangladesh is one of the countries that have various kinds of diseases among its vast population, throughout the year in different places. It is becoming a very crucial factor in the medical sector to be cautious regarding the health of people. In this paper, a prediction model is provided to represent the geo-temporal disease prediction model. This model will help people to be aware of their health according to location and season. We made a visualization representation that can demonstrate the disease prediction model. The proposed disease prediction model is constructed in such a way that it can find out the occurrences of the inputted disease in a given time and place. By implementing the algorithm on the mentioned medical data, missing values were replaced by our proposed missing value filter algorithm SVM. Then from the historical medical data, we analyzed the frequently occurring diseases along with geo-temporal relations. Moreover, after training the system with our specified analysis, the future disease prediction model was made with respect to the geo-temporal relation. We revealed the empirical result by which our application is useful and can be used in the real world for predicting future diseases in Bangladesh using geo-temporal location.