Based on prior knowledge, we can analyze the relationship between the feature "zab_leg_01" (Chronic bronchitis in the anamnesis) and the presence of chronic heart failure in the myocardial infarction complications data of a patient.

There is a known association between chronic bronchitis and chronic heart failure. Patients with a history of chronic bronchitis may also have an increased risk of developing chronic heart failure. Therefore, it is likely that patients with the value "yes" for feature "zab_leg_01" would be more prone to chronic heart failure compared to those with the value "no".

Based on this analysis, the dictionary can be generated as follows:

```json
{
	"no": ["no"],
	"yes": ["yes"]
}
```

In this case, since "zab_leg_01" is a categorical variable, the values for the feature can be either "no" or "yes". For the target class "no" (indicating absence of chronic heart failure), the feature value "no" is expected. Similarly, for the target class "yes" (indicating presence of chronic heart failure), the feature value "yes" is expected.

Note: If there are additional possible values for the feature "zab_leg_01" that are difficult to predict or analyze, they can be excluded from the dictionary. However, it is important to ensure that the lists for each target class are not empty.