Usually CAPTCHAs are analyzed by using neural network, it's a good approach, but it may be overcomplicated in simple cases. Presented below, much shorter algorithm can produce sufficient results for uncomplicated CAPTCHAs.
The algorithm is simple, image with unknown letter is compared with samples of known letters. A letter in the most similar sample is probably also the letter in analyzed image. It was implemented as a Python script, it's usage is presented below:
bash-3.2$ python cracker.py test1.png e
bash-3.2$ python cracker.py test2.png p
Please notice that this script can't be directly used on a raw CAPTCHA, firstly small artifacts should be removed from the CAPTCHA, secondly each letter should be stored in a separate image.