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 Decision tree (DT) approach utilizing meteorological data. Materials and Methods: For predicting the accuracy percentage of network performance for allocating server resources in information technology infrastructure, the Novel Linear Regression algorithm (LR) with sample size=10 and with sample size = 10, 95 percent confidence interval, and pretest power of 80 percent were iterated at various times. The Novel Linear Regression transforms the data into a higher-dimensional space, which improves accuracy. Results: When compared to the accuracy of Decision Tree (80%), Novel Linear Regression appears to be more accurate (88%). There was a insignificant difference between LR and the Decision Tree with (p=0.936) (p<0.05) as shown in Table 3. As demonstrated in Table 3, there was a significant relationship between LR and the Decision Tree (p=0.001) two tailed (p>0.05). Conclusion: Novel Linear Regression algorithm performed more effectively than Decision Tree for predicting network performance.