It helps to visualise conditional probability problems.
For example, if you toss a coin twice, and you would like to work out the probability of obtaining 2 heads in a row. You would tree diagram a simple plot like this with the relevant probabilities: One thing to not is the sum of the probabilities from each 'node' of the branch should always add to precisely 1 - in this case the chances of heads and tails are equal so you have a 0.5 chance of obtaining either.
To find the probability we find all the branches which lead to the desired outcome, in this case there is just one, and we multiply the probabilities together. So the probability of obtaining to heads is 0.5 x 0.5 = 0.25
If we wanted to workout the probability of obtaining a heads and then tails in any particular order, you would look at both branches which lead to this outcome. In this case there are 2:
Work out the relevant probability from both branches, in this case the chance of going down each branch is 0.5 x 0.5 = 0.25. We then add these probabilities together (0.25 + 0.25) to obtain a probability of 0.5 of obtaining a heads and a tails, or a tails then heads. Makes sense when you think about it!
That covers the basics, you can add a further branch to work out probabilities of different outcomes from more than 2 coin tosses, and use it to model more complex events with differing probabilities.