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Cricket is an outdoor game which consists of 2 teams, each having 11 players, out of the two teams, one bats and the other one bowls and fields. There are various formats of cricket like Test cricket, ODI (One Day Internationals) cricket, and T-20 cricket. Test cricket format takes 5 days to reach to a decision which can be in Win, lose or Draw. Due to reduced playtime and speedy decision, nowadays T20 cricket is widely popular. Due to the popularity of T-20 across cricketing nations; many countries have started their own leagues. In India, IPL (Indian Premier League) is very much popular. Now-a-days team's management is using various technologies to improve their team's performance and also takes the help of various technologies to analyze the opposite team's performance. Prediction of the score is one of the most important events in cricket. Once the score prediction is done, the chasing team prepares itself accordingly. We use deep learning and ML algorithms for finding the first inning's predicted score. In the current work, we have used Linear Regression, Ridge Regression for model building and plot various graphs and find the errors to evaluate our model. In this model, we have used the IPL dataset taken from Kaggle and cleaned it using various available techniques. After building the model, we have analysed it by finding errors. Then we have deployed it in the graphical userinterface that was built with the help of HTML and Flask. [ABSTRACT FROM AUTHOR]