This study helps to forecast the Infrared Radiations from the top of the atmosphere over six cities in Pakistan using data gathered over a ten-year period from the Synoptic Top of the Atmosphere (TOA) and surface fluxes and clouds Edition 4A, a data product of clouds and the Earth's Radiant Energy System which gathers daily ten-year local weather data. This work aims to use exploratory data analysis to examine infrared radiation quantification. The assessment of infrared radiations from the upper atmosphere, a crucial part of the Earth's radiation budget with consequences for climate modeling and satellite based atmospheric research, is the main emphasis of this work. In order to accomplish this, atmospheric datasets taken from the NASA Earth observation gateway used in artificial neural network (ANN) modeling. By combining machine learning with NASA's atmospheric datasets for Top of the Atmosphere (TOA) infrared radiation evaluation, this work is new in that it offers efficiency and accuracy gains over traditional methods. Artificial neural network (ANN) utilized in the Pakistani cities of Karachi, Thatta, Mirpurkhas, Gilgit, Kalam, and Astore to predict average daily infrared variation. Over the course of seven years, the network trained, validated, and tested using infrared flux data from 2011 to 2018. With the aid of the hidden layer's training and validation settings, the average daily infrared flux estimated. We will be able to investigate the changes in Earth's climate throughout time, which impact by various factors, thanks to research of this kind. Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), correlation coefficient, Root Mean Square Error (RMSE), and Mean Bias Error (MBE) calculated for the purposes of validating the statistical errors. The statistical errors demonstrate that the neural network model predicts infrared radiations for Thatta city well, while average predictions generated for Astore, Gilgit, and Kalam, and Mirpurkhas city, respectively. Astore exhibits the best correlation, followed by Thatta, Karachi, Kalam, Gilgit, and Mirpurkhas.