Choice of ML classifer doesn’t drastically alter the results. For example, a fine tuned well generalized logistic regression model will serve comparable to a random forest, on a given dataset. However, the process of training and fine tuning might be subtly different. So if you are unsure, go with the model that you are confident with and follow good data science practices.