This thesis aims to answer two questions about causal claims (such as sentences containing cause or because). Firstly, the modelling question: what kind of information do we use when we judge that a causal claim holds? Secondly, the meaning question: under what conditions do we judge that a causal claim is true? Our answer to the modelling question is that a causal model must contain time, part–whole structure, and nomic possibility. The model represents scenarios as extended in time, with each moment in time having a mereological structure (the mereological structure tell us, for example, that the state of Amsterdam is part the state of the Netherlands). The notion of nomic possibility specifies which worlds are nomically possible and which worlds are nomically impossible; in other words, which worlds satisfy the laws and which do not. In addition, the model must also contain two language-related components. For each sentence, the model must tell us what parts of the world the sentence is about, and in which worlds it is true. We show that this modelling framework is strictly more general than a popular alternative, that of structural causal models. Every structural causal model can be translated into our framework, and therefore every scenario that structural causal models can represent our framework can represent too. However, the converse does not hold. There are some scenarios that our proposed model can represent which structural causal models cannot. Our answer to the meaning question appeals to two relations: sufficiency and production. We propose that the meaning of cause and because is a blend of these relations: C cause E and E because C are true just in case C is true, and C is sufficient to produce E but C’s negation is not.