Glass is one of the commonly used materials with exceptional properties such as high mechanical strength, high chemical resistance, and low dielectric coefficient. Over the past decade, laser has been developed as a promising tool for welding between similar and dissimilar materials, especially glass and metals. Aluminum is also a commonly used material, which is known for its light weight, high conductivity, and high specific strength. In this study, we conducted a glass-to-aluminum welding experiment using lasers, reported the welding results, and analyzed the influential factors of the welding strength caused by the laser system, including power, repetition rate, scanning speed, and scanning cycles. From the analysis, we found that power, scanning cycles, and interactions of the laser parameters are significantly important to the welding strength. Moreover, we built a logistic regression model to predict whether a welding sample can have a strong connection between glass and aluminum given the laser parameters. The results indicate that our model can achieve maximum accuracy of 81.2% for the prediction task. Therefore, our findings can fill the gap from previous studies that were lack of statistical data analysis and prediction tasks in glass-to-aluminum welding, and further enhance the welding quality in future studies.