The take-off phase is identified as critical to the success or failure of a flight mission, with appropriate climb altitudes being essential to ensure successful take-off. To predict and assess abnormal phenomena in climb altitudes, this paper investigates the key predictive parameters that lead to abnormal climb altitudes. The research is based on a virtual reality (VR) flight simulator, focusing on the take-off phase of the Cessna152 aircraft model. Thirty-one participants were recruited to engage in simulated flight tasks, resulting in the collection of 180 effective data samples from novice flights. Based on the simulator's Quick Access Recorder (QAR) data, key QAR parameters that affect abnormal climb altitudes were identified through clustering and correlation analysis. Subsequently, regression analysis was employed to explore the relationship between these key parameters and the abnormality in climb altitudes. The findings of the study indicate that the average flight speed and maximum pitch angle are the primary QAR parameters influencing flight altitude, jointly accounting for 70.2% of the abnormality in climb altitudes.