Based on my prior knowledge, credit history can have an impact on whether a person receives credit or not. Lenders usually consider a person's previous credit behavior to evaluate their creditworthiness. By analyzing the relationship between the feature "credit_history" and the task "Does this person receive a credit?", we can identify the possible values of credit_history for both the "yes" and "no" classes.

Here is the analysis:

- Possible values of credit_history for target class "yes":
  - existing paid
  - all paid

- Possible values of credit_history for target class "no":
  - critical/other existing credit
  - delayed previously
  - no credits/all paid

Based on this analysis, I will create the dictionary:

```json
{
	"yes": ["existing paid", "all paid"],
	"no": ["critical/other existing credit", "delayed previously", "no credits/all paid"]
}
```