Analog and mixed-signal diagnosis is a subject rarely visited in teaching literature. Probably, the reason for that is the need for deep understanding of the functionality of the circuits in conjunction with implementation of complex algorithms frequently being very specific to this subject. In any case, in this chapter we will try to list and elaborate several deterministic algorithms that cover processing of different measured signals and implement different inference concepts. A tendency to reduction of the number of measurement points will be followed making both the process tractable and easy to understand. In that, DC, frequency, and time domain signals will be considered as well as linear and nonlinear circuits. Special attention will be paid to hierarchical diagnosis enabling to tackle complex systems as well as mixed-signal ones. In that, artificial neural networks will be promoted as an indispensable tool to capture the circuit properties and to select among hypotheses.