Theoretical prediction of essential genes in Plasmodium falciparum 3D7 genome shows significant importance in the fight against malaria. The sequence feature with the virtues of generality across organisms and accessibility could be used to predict essential gene. In this study, we used an ensemble model with two base estimators: a SVM model and a LGBM model to measure the prediction ability of the sequence feature. It could be seen that the sequence feature extracted by the w-Nucleotide Z Curve had the ability to predict essential gene. The prediction accuracy increased as the number of the variables increased till w equaled 3 or 4. Then as the number of the variable increased, the redundant variables appeared. When the redundant variable were removed by Recursive Feature Elimination method, the performance of the model could be improved.