Aim: The major goal of this study is to evaluate the accuracy of the Novel Linear Regression technique for forecasting network performance for allocating server resources to the Random Forest (RF) approach utilizing meteorological data. Materials and Methods: The Novel Linear Regression algorithm (LR) with sample size=10, 95 percent confidence interval, and pretest power of 80 % was iterated at various times to predict the accuracy percentage of network performance for allocating server resources in technology infrastructure. Novel Linear Regression allows for more accuracy by transforming data into a higher-dimensional space. Results: Novel Linear Regression appears to prove with better accuracy (88%) compared to Random Forest accuracy (74%). There was an insignificant difference between LR and RF with p=0.818 (p<0.05). Conclusion: For estimating network performance, Novel Linear Regression performed with better accuracy compared to Random Forest.