diff --git a/src/main/java/ru/ulstu/fc/rule/service/FuzzyInferenceService.java b/src/main/java/ru/ulstu/fc/rule/service/FuzzyInferenceService.java
new file mode 100644
index 0000000..70a9746
--- /dev/null
+++ b/src/main/java/ru/ulstu/fc/rule/service/FuzzyInferenceService.java
@@ -0,0 +1,127 @@
+package ru.ulstu.fc.rule.service;
+
+import com.fuzzylite.Engine;
+import com.fuzzylite.term.Activated;
+import com.fuzzylite.variable.InputVariable;
+import com.fuzzylite.variable.OutputVariable;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.stereotype.Service;
+
+import java.util.Map;
+import java.util.stream.Collectors;
+
+@Service
+public class FuzzyInferenceService {
+    private final static Logger LOG = LoggerFactory.getLogger(FuzzyInferenceService.class);
+    private final static String OUTPUT_VARIABLE_NAME = "state";
+    private final static String RULE_TEMPLATE = "if %s is %s and %s is %s then "
+            + OUTPUT_VARIABLE_NAME
+            + " is %s";
+    private final static String NO_RESULT = "Нет результата";
+
+//    private List<String> mapRulesToString(List<DbRule> dbRules) {
+//        return dbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
+//    }
+
+//    private String getFuzzyRule(DbRule dbRule) {
+//        return format(RULE_TEMPLATE,
+//                dbRule.getFirstAntecedent().name(),
+//                dbRule.getFirstAntecedentValue().getAntecedentValue(),
+//                dbRule.getSecondAntecedent().name(),
+//                dbRule.getSecondAntecedentValue().getAntecedentValue(),
+//                dbRule.getId());
+//    }
+
+//    private RuleBlock getRuleBlock(Engine engine,
+//                                   List<DbRule> dbRules,
+//                                   Map<String, Double> variableValues,
+//                                   List<AntecedentValue> antecedentValues,
+//                                   List<Integer> consequentValues) {
+//        variableValues.forEach((key, value) -> {
+//            InputVariable input = new InputVariable();
+//            input.setName(key);
+//            input.setDescription("");
+//            input.setEnabled(true);
+//            input.setRange(-1, 1);
+//            input.setLockValueInRange(false);
+//            input.addTerm(new Triangle("спад", -1, 0));
+//            input.addTerm(new Triangle("стабильно", -0.1, 0.1));
+//            input.addTerm(new Triangle("рост", 0, 1));
+//            engine.addInputVariable(input);
+//        });
+//
+//        OutputVariable output = new OutputVariable();
+//        output.setName(OUTPUT_VARIABLE_NAME);
+//        output.setDescription("");
+//        output.setEnabled(true);
+//        output.setRange(0, consequentValues.size() + 0.1);
+//        output.setAggregation(new Maximum());
+//        output.setDefuzzifier(new Centroid(10));
+//        output.setDefaultValue(Double.NaN);
+//        output.setLockValueInRange(false);
+//        for (int i = 0; i < consequentValues.size(); i++) {
+//            output.addTerm(new Triangle(consequentValues.get(i).toString(), i, i + 1));
+//        }
+//        engine.addOutputVariable(output);
+//
+//        RuleBlock mamdani = new RuleBlock();
+//        mamdani.setName("mamdani");
+//        mamdani.setDescription("");
+//        mamdani.setEnabled(true);
+//        mamdani.setConjunction(new Minimum());
+//        //mamdani.setDisjunction(null);
+//        mamdani.setImplication(new AlgebraicProduct());
+//        mamdani.setActivation(new General());
+//        mapRulesToString(dbRules).forEach(r -> {
+//            LOG.info(r);
+//            mamdani.addRule(Rule.parse(r, engine));
+//        });
+//        return mamdani;
+//    }
+
+    private Engine getFuzzyEngine() {
+        Engine engine = new Engine();
+        engine.setName("Fuzzy rules");
+        engine.setDescription("");
+        return engine;
+    }
+
+//    public List<Assessment> getFuzzyInference(List<DbRule> dbRules,
+//                                              List<AntecedentValue> antecedentValues,
+//                                              Map<String, Double> variableValues) {
+//        validateVariables(variableValues, dbRules);
+//        variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
+//        Engine engine = getFuzzyEngine();
+//        List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
+//        engine.addRuleBlock(getRuleBlock(engine, dbRules, variableValues, antecedentValues, consequentValues));
+//        Map<String, Double> consequents = getConsequent(engine, variableValues);
+//        if (consequents.containsKey(NO_RESULT)) {
+//            return new ArrayList<>();
+//        }
+//        List<Assessment> assessments = new ArrayList<>();
+//        for (Map.Entry<String, Double> consequent : consequents.entrySet()) {
+//            for (DbRule dbRule : dbRules) {
+//                if (dbRule.getId().equals(Integer.valueOf(consequent.getKey()))) {
+//                    assessments.add(new Assessment(dbRule, consequent.getValue()));
+//                }
+//            }
+//        }
+//        return assessments;
+//    }
+
+    private Map<String, Double> getConsequent(Engine engine, Map<String, Double> variableValues) {
+        OutputVariable outputVariable = engine.getOutputVariable(OUTPUT_VARIABLE_NAME);
+        for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
+            InputVariable inputVariable = engine.getInputVariable(variableValue.getKey());
+            inputVariable.setValue(variableValue.getValue());
+        }
+        engine.process();
+        if (outputVariable != null) {
+            LOG.info("Output: {}", outputVariable.getValue());
+        }
+        return Double.isNaN(outputVariable.getValue())
+                ? Map.of(NO_RESULT, 0.0)
+                : outputVariable.fuzzyOutput().getTerms().stream().collect(Collectors.toMap(t -> t.getTerm().getName(), Activated::getDegree));
+    }
+}