The aim is to find movie ratings using logistic regression and comparing the result with naive bayes based on Accuracy. A total of 6040 samples were collected from movie datasets available in kaggle. Two algorithms are used; one is Logistic Regression and another is naive bayes algorithm. The computation processes were executed and verified for exactness. Sample size N=5 is taken for both algorithms. SPSS was used for predicting significance value of the dataset considering G-Power value as 80%. Logistic Regression achieved mean accuracy of 80.83% when compared to Naive Bayes Algorithm with 82.53%. Results were obtained with a level of significance with 0.003 (p<0.05). Applied strange recommendation model confirms to have higher accuracy than Naive Bayes algorithm.