Genetic algorithm (GA) plays an important role, as heuristic search techniques for handling complex spaces, in many domains such as artificial intelligence, data analysis, engineering, robotic, etc. The genetic processes on the natural evolution principles of populations have been fairly successful at solving complex problems and produce optimal (near optimal) solution from generation to generation. This is applied in students’ quantitative data analysis to identify the most impact factor in their performance in their curriculum. The results will help the students as well as educational institutions to improve the quality of teaching after evaluating the marks achieved by the students’ in academic career. Also used some different crossover in Genetic Algorithm for analysis and comparative study of results. So proposed genetic algorithm with different crossover with new student analysis model to find the most impacting factor in students performance.