Aiming at the problem of whether the color difference exceeds the threshold when the RGB-LED is lit and how to calibrate the deviation, this article proposes an RGB LED chromaticity parameter prediction and calibration algorithm. This article is divided into two parts for the intelligent prediction and calibration method of RGB LED chromaticity parameters. The first is the color difference prediction part. First, combining the ideas of random forest and XGBoost, this article designs a classification algorithm and named it RF-XGBoost. Use RF-XGBoost to predict whether the color difference exceeds 0.0055 when the RGB lamp lights up 30 colors. Compared with decision tree, random forest, and XGBoost, RF-XGBoost performs better in recall rate through comparative experiment analysis. The second is the color correction part. Aiming at the problem of excessive color difference when RGB-LED is lit, this article proposes the cor-calibration color calibration algorithm. The function relation between chromaticity coordinate and error model is established. The current error compensation model, automatic selection of calibration step, and closed-loop calibration are used to calibrate the colors beyond the error. Compared with the existing calibration algorithm, after using the cor-calibration algorithm, the color pass rate in the color gamut increased from 91.25% to 99.79%. Experiments show that the RF-XGBoost algorithm and the cor-calibration algorithm can achieve precise screening and high-precision calibration of RGB-LEDs.