I am trying to predict if students could meet their assignments deadline or not based on days to complete and number of other assignments that they are supposed to complete. I found out that: There is no spearman or pearson correlation (close to 0) between inputs and output. This is clear from the plots as well. I built a binary logistic regression on this data and the model doesn't fit. Since there might be a nonlinear relation between inputs and output, I also built a neural network and error was so high. Could it be concluded that I can't predict the output based on these input variables?
My guess is that you're right: you can't accurately predict the dependent variable using these features. Since your models have training errors near the base rate, the features don't seem to have much predictive value. It's possible, but very unlikely, that a predictively useful relationship exists that neither the logistic-regression model nor the neural network was able to capture.