The wrong decisions wasted billions, efforts, and time each year, but , lately reliance on the data in decisions become obligatory, which reduce the wrong decisions possibility, and instead of rely on the human experience, the date became our fascinating guide, so we tried to provide an informative and valuable information for decision makers and decision makers in the transport and road sector, this project help to predict the traffic volume in the future based on historical time-series data, detect the abnormal behaviour, two approaches were used here for prediction Regression using Xgboost and Time-Series prediction using ARIMA & SARIMAX & Extra Trees regressor, and three techniques for anomaly detection using Deviation & Seasonal & STL methods, and the project success to predict the traffic at next 8 hours with MAPE less than 4%.