Diamond prices have been exceedingly variable during the last century. In this research, we describe a machine learning-based strategy for predicting diamond prices in order to avoid human error. There is a lot lower danger of losing the investment with an accuracy of 98% utilizing Random Forest Regression. Linear regression, Lasso regression, Support Vector Regression, and Random Forest are all used in the proposed machine learning-based prediction model. The proposed technique predicts the value most correctly. We've also introduced a Crontab tool to automate the process, which will retrain the model to the most correct value before the diamond market opens