Total Probability Rule/Bayes Formula

Just wondering if I am the only one that is really struggling with questions relating to the Total Probability rule? I’m solid with everything else in Quants and the Probability Concepts reading but for whatever reason, questions relating to this I just can’t grasp. Any recommendations or am I the only one that this is not clicking for?

Thanks.

Not sure if it helps, but for me it’s really useful to draw it out in a tree. Then it makes sense how to get to P(B) through conditional probabilities. Image result for conditional probability tree

What I don’t get is how the formula is:

(Probability of new information / Unconditional Probability of New Information) * Prior Probability of Event

However, whenever it is applied in an example or question we do this:

(Conditional probability of event / Unconditional Probability of Event)

Where are the probabilities of the new information and why aren’t we multiplying by the prior probability of the event.

I’m curious, how do you paste images onto the forum? I couldn’t figure it out, thanks.