To increase accuracy for the prediction of agriculture insurance claim cost based on crop insurance data.Gradient Boosting Machine (LGBM) and linear regression models are tested with total Samples 6022 for n=7 iterations to predict accuracy. LGBM works based on decision tree algorithm and linear based on fitted regression equation. The coefficient of determination values of proposed LGBM regression (92.52%) and linear regression (72.47%) are obtained. There was a statistical significance between LGBM regression and linear regression (p=0.001).Prediction of agriculture insurance claim cost LGBM regression technique produces significantly better performance than the linear regression technique.